System and method for establishing bidirectional links between multiphysics modeling and design systems

ABSTRACT

A system and method for implementing, on one or more processors, a bidirectional link between a design system and a multiphysics modeling system includes establishing via a communications link a connection between the design system and the multiphysics modeling system. Instructions are communicated via the communication link that include commands for generating a geometric representation in the design system based on parameters communicated from the multiphysics modeling system. One or more memory components can be configured to store a design system dynamic link library and a multiphysics modeling system dynamic link library. A controller can be operative to detect an installation of the design system, and implement via the dynamic link libraries, bidirectional communications of instructions between the design system and the multiphysics modeling system.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to and the benefits of U.S. Provisional Application No. 61,290,839, filed on Dec. 29, 2009, U.S. Provisional Application No. 61/360,038, filed Jun. 30, 2010, and U.S. Provisional Application No. 61/377,841, filed on Aug. 27, 2010; this application is also a continuation-in-part of U.S. patent application Ser. No. 12/487,762, filed on Jun. 19, 2009, which is a continuation of U.S. patent application Ser. No. 10/042,936, filed on Jan. 9, 2002, now issued as U.S. Pat. No. 7,596,474, which is a continuation-in-part of U.S. patent application Ser. No. 09/995,222, filed on Nov. 27, 2001, now issued as U.S. Pat. No. 7,519,518, which is a complete application claiming priority to and the benefit of U.S. Provisional Application No. 60/253,154, filed on Nov. 27, 2000, and U.S. patent application Ser. No. 09/995,222 is also a continuation-in-part of U.S. patent application Ser. No. 09/675,778, filed on Sep. 29, 2000, now issued as U.S. Pat. No. 7,623,991, which is a complete application claiming priority to and the benefit of U.S. Provisional Application No. 60/222,394, filed on Aug. 2, 2000; the disclosures of each of the foregoing applications are hereby incorporated by reference herein in their entirety.

FIELD OF THE INVENTION

The present invention relates generally to systems and methods for modeling and simulation, and more particularly, to interfaces and communications between design systems and multiphysics modeling systems.

BACKGROUND

Computer-aided design systems are typically used to develop product designs and may be complemented with packages analyzing a single aspect of a design, such as, structural analysis in conjunction with computer-aided design systems. It would be desirable to have design systems that can operate in more complex environments.

SUMMARY OF THE INVENTION

According to one aspect of the present disclosure, a method is executable on one or more processors for implementing a bidirectional link between a design system and a multiphysics modeling system. The method includes the acts of establishing via a communications link a connection between the design system and the multiphysics modeling system. Instructions are communicated via the communication link. The instructions are configured to include commands for generating a geometric representation in the design system based on parameters communicated from the multiphysics modeling system.

According to another aspect of the present disclosure, a method is executable on one or more processors for implementing a bidirectional link between a design system and a multiphysics modeling system. The method includes the acts of detecting the design system, and communicating instructions between the detected design system and the multiphysics modeling system. The instructions include commanding the design system to generate a geometric representation based on parameters received from the multiphysics modeling system.

According to another aspect of the present disclosure, a system is configured to establish a bidirectional link between a design system and a multiphysics modeling system. The system includes one or more memory components configured to store a design system dynamic link library and a multiphysics modeling system dynamic link library. A controller is operative to detect an installation of the design system, and implement via the dynamic link libraries, bidirectional communications of instructions between the design system and the multiphysics modeling system.

According to yet another aspect of the present disclosure, one or more non-transitory computer readable media are encoded with instructions, which when executed by at least one processor associated with a design system or a multiphysics modeling system, causes the at least one processor to perform the above method(s).

Additional aspects of the present disclosure will be apparent to those of ordinary skill in the art in view of the detailed description of various embodiments, which is made with reference to the drawings, a brief description of which is provided below.

BRIEF DESCRIPTION OF THE DRAWINGS

Features and advantages of the present disclosure will become more apparent from the following detailed description of exemplary embodiments thereof taken in conjunction with the accompanying drawings in which:

FIG. 1 illustrates an exemplary aspect of a computer system;

FIG. 2 illustrates an exemplary aspect of software that may reside and be executed in one of the hosts of FIG. 1;

FIG. 3 illustrates an exemplary aspect of a graphical user interface for selecting exemplary application modes;

FIG. 4 illustrates an exemplary aspect of a graphical user interface for selecting physical properties on subdomains for an exemplary heat transfer application mode;

FIG. 5 illustrates an exemplary aspect of a graphical user interface for specifying physical properties on boundaries for an exemplary heat transfer application mode;

FIG. 6 illustrates an exemplary aspect of a graphical user interface for modifying partial differential equations in “coefficient view”;

FIG. 6A is an example of an exemplary aspect of a data structure that may be used in connection with data for each application mode selected and also in connection with storing data for the combined partial differential equation system of application modes;

FIG. 7 illustrates an exemplary aspect of a graphical user interface for specifying the ability to solve for any subset of the physical quantities;

FIG. 8 is an example of an embodiment of a coefficient form partial differential equation format;

FIG. 9 is an example of a general form partial differential equation format;

FIG. 10 is an example of formulae that may be used in an embodiment in solving for non-linear systems of equations in connection with performing substitutions for linearization;

FIG. 11 is an example of formulae that may be used when performing a conversion from coefficient to general form;

FIGS. 12 and 13 are examples of formulae that may be used in solving for equations in coefficient and general form;

FIG. 14 is an example of formulae that may be used when approximating the solution with a function from a finite-dimensional function space;

FIGS. 15 and 16 are examples of formulae that may be used in connection with solving systems of equations in coefficient form;

FIG. 17 is an example of an embodiment of formulae that may be used in connection with solving equations in the general form;

FIG. 18 is an example of the representation of finite element discretization in accordance with conditions of formulae of FIGS. 15 and 16;

FIG. 19 is an example of formulae that may be used in connection with solving equations in the coefficient form;

FIG. 20 is an example of formulae that may be used in connection with solving equations in the general form;

FIG. 21 is an example of an iteration formula that may be used in connection with solving equations in general form;

FIG. 22 and FIG. 23 form a flowchart of method steps of an exemplary aspect for specifying one or more systems of partial differential equations, representing them in a combined form, and solving a combined system of partial differential equations;

FIG. 24 is an example of a representation of a class hierarchy that may be included in an embodiment in connection with predefined and user defined application modes;

FIG. 25 is an example of one dimensional predefined application modes that may be included in an embodiment;

FIG. 26 is an example of two dimensional predefined application modes that may be included in an embodiment;

FIG. 27 is an example of properties of an application mode;

FIG. 28 is an example of a class constructor that may be used to create a user defined application or application mode;

FIG. 29 is an example of methods that may be included in an embodiment for an object class;

FIG. 30 is an example of a GUI that may be displayed in connection with a user-defined application;

FIG. 31 is an example of formulae that may be used in connection with the user-defined application of FIG. 30;

FIG. 32 is an example of a constructor used in creating the user-defined application of FIG. 30;

FIG. 33 and FIG. 34 are examples of fields that may be included in a user-defined portion of a data structure used in connection with the user-defined application of FIG. 30; and

FIG. 35 includes examples of fields that may be included in a data structure used to define a geometric object used in connection with the user-defined application mode of FIG. 30;

FIG. 36 is an example of another embodiment of a user interface that may be used in connection with specifying local and non-local couplings of multiphysics systems;

FIG. 37 is an example of a Boundary settings dialog box;

FIG. 38 is an example of a Subdomain Settings dialog box;

FIG. 39 is another example of a Subdomain Settings dialog box;

FIG. 40 is an example of a representation of the data structure that may be included in an embodiment in connection with storing data in connection with the PDEs selected and combined;

FIG. 41 is an example of a weak formulation;

FIG. 42 is an example of a conversion from general form to weak form;

FIG. 43 is an example of a Point Settings dialog box;

FIG. 44 is an example of an Edge Settings dialog box;

FIGS. 45A-C illustrate various pages of a Coupling Variable Settings dialog box, respectively showing a Variables page, Source page and Destination page;

FIGS. 46 and 47 respectively show examples of a Variables page and a Definition page of an Expression Variable Settings dialog box;

FIGS. 48-50 are flowcharts of processing steps in an exemplary aspect for forming and solving a system of partial differential equations of a combined system;

FIG. 51 is a flowchart of processing steps in an embodiment for solving a system of PDEs;

FIG. 52 is a flowchart of processing steps in an embodiment for computing the stiffness matrix;

FIG. 53 is a flowchart of processing steps in an embodiment for computing the residual matrix;

FIG. 54 is a flowchart of processing steps in an embodiment for determining the constraint matrix;

FIG. 55A is a flowchart of processing steps in an embodiment for determining a constraint residual;

FIGS. 55B-55M are flowcharts of processing steps in an embodiment for determining the Jacobian and values of different types of variables;

FIGS. 56-57 are examples of data structures that may be included in an embodiment in connection with the extended mesh structure for multiple geometries;

FIGS. 58-75 are examples of embodiments of screenshots that may be used in an embodiment of the computer system of FIG. 1; and

FIG. 76 is a screen shot of a graphical user interface for a coupling variables settings dialog box;

FIG. 77 is a graph of an example of Poisson's equation on a single rectangular domain;

FIGS. 78A-78B are graphs of examples of scalar couplings;

FIG. 79 is a graph of another example of Poisson's equation on a single rectangular domain;

FIGS. 80A-80C are graphs of examples of extrusion couplings;

FIGS. 81A-81C are graphs of examples of projection couplings;

FIG. 82 is a diagram of a packed bed in a reactor;

FIG. 83 is another screen shot of a graphical user interface for the coupling variables settings dialog box;

FIG. 84 is a screen shot of a graphical user interface for a concentration plot;

FIG. 85 is a graph of a three-dimensional plot;

FIG. 86 is a perspective view of a magnetic brake;

FIG. 87 is a screen shot of a graphical user interface for a draw mode;

FIG. 88 is a screen shot of a graphical user interface for an expressions variable settings;

FIG. 89 is a screen shot of a graphical user interface for an expressions variable settings;

FIG. 90 is a screen shot of a graphical user interface for mesh parameters;

FIG. 91 is a screen shot of a graphical user interface for a solution to the entered parameters in FIG. 90;

FIGS. 92-95 are screen shots of graphical user interfaces for the coupling variables settings;

FIG. 96 is a screen shot of a graphical user interface for cross-section plot parameters; and

FIGS. 97A-97B are graphs of plots for ω and dω/dτ.

FIG. 98 illustrates an exemplary aspect of a design system interface for communicating with and accessing model settings of an associated multiphysics modeling system.

FIG. 99 illustrates an exemplary aspect of communications in a bidirectional link between a design system and a multiphysics modeling system.

FIG. 100 illustrates an exemplary graphical user interface in a multiphysics modeling system for establishing a link to a design system.

FIG. 101 illustrates exemplary dynamic link library operations for a bidirectional link between a multiphysics modeling system and a design system.

FIG. 102 illustrates an exemplary aspect of a bridge connection for communications between a design system and a multiphysics modeling system.

FIG. 103 illustrates an exemplary aspect of a bridge connection for communicating between a multiphysics modeling system and a design system user interface.

FIG. 104 illustrates an exemplary aspect for dynamically controlling, via a bidirectional link, parametric and geometric features between a design system and a multiphysics modeling system.

FIG. 105 illustrates another exemplary aspect for dynamically controlling, via a bidirectional link, parametric and geometric features between a design system and a multiphysics modeling system.

FIG. 106 illustrates another exemplary aspect for dynamically controlling, via a bidirectional link, parametric and geometric features and associativity operations to set physical properties and boundary conditions in a multiphysics modeling system.

FIG. 107 illustrates an exemplary graphical user interface in a multiphysics modeling system for dynamically controlling features between the multiphysics modeling system and a design system.

FIG. 108 illustrates an exemplary process for defining variations of parameters controlling geometric features in a design system.

FIG. 109 illustrates an exemplary graphical user interface for defining parameter variations.

FIG. 110 illustrates an exemplary process for generating a model tree within a multiphysics modeling system.

FIG. 111 illustrates an exemplary process for forming and solving a system of partial differential equations in a multiphysics modeling system based on operations represented in a model tree.

FIG. 112 illustrates an exemplary aspect of a model tree for forming and solving multiphysics problems in a multiphysics modeling system.

FIG. 113 illustrates an exemplary aspect of a physics node of a model node for a model tree that includes operations for generating physical quantities and boundary conditions for a multiphysics problem.

FIG. 114 illustrates an exemplary aspect of a window for a node of a model tree for entering settings that define model operations for a multiphysics problem.

FIG. 115 illustrates an exemplary aspect of a physics node of a model node that has an additional node for describing selected physical quantities for a multiphysics problem.

FIG. 116 illustrates an exemplary aspect of a physics node of a model node describing operations representing contributions to the physical quantities of a multiphysics problem.

FIG. 117 illustrates an exemplary window for adding contributions to the physical quantities associated with a physics node.

FIG. 118 illustrates an exemplary model tree having a plurality of nodes including the identification of exclusive operation(s) associated with a selected node.

FIG. 118 illustrates an exemplary model tree having a plurality of nodes including the identification of non-exclusive operation(s) associated with a selected node.

FIG. 120 illustrates an exemplary aspect of a model tree including a plurality of nodes for which settings of each of the model nodes can be accessed to allow the formation and solving of a multiphysics problem on a multiphysics modeling system.

While the present disclosure is susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described in detail herein. It should be understood, however, that the invention is not intended to be limited to the particular forms disclosed. Rather, the invention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION

While the present disclosure is susceptible of embodiment in many different forms, there is shown in the drawings and will herein be described in detail various aspects of the invention with the understanding that the present disclosure is to be considered as an exemplification of the principles of the invention and is not intended to limit the broad aspect of the invention to the aspects illustrated.

Computer systems may be used for performing a variety of different tasks by executing one or more computer programs stored on computer readable media (e.g., temporary or fixed memory, magnetic storage, optical storage, electronic storage, other non-transitory media, flash memory). A computer program may include instructions which, when executed by a processor, perform one or more tasks. In certain embodiments, a computer system may execute machine instructions, as may be generated, for example, in connection with translation of source code to machine executable code, to perform modeling, simulation, and problem solving tasks. One technique which may be used to model systems is to represent various physical aspects of the system being modeled in terms of equations or in other quantifiable ways that may be processed by a computer system. In turn, these equations or other quantifiable ways may be solved by a computer system configured to solve for one or more variables associated with the equation, or the computer may be configured to solve a problem using other received input parameters.

It is contemplated that computer applications for modeling a system may provide many advantages particularly as the complexity of the model and the system being modeled increases. In certain embodiments a user may be able to combine one or more systems that are each represented by different models, into a multiphysics modeling system. Multiphysics modeling systems typically involve multiple physical models or multiple simultaneous physical phenomena. For example, combining chemical kinetics and fluid mechanics or combining finite elements with molecular dynamics. Multiphysics modeling can also include solving coupled systems of partial differential equations. Exemplary multiphysics modeling systems include the COMSOL® 4.0 or COMSOL Multiphysics® simulation software operating on a computer system, as such software is available from COMSOL, Inc. of Burlington, Mass. Additional exemplary aspects of multiphysics modeling systems are described in U.S. patent application Ser. No. 10/042,936, filed on Jan. 9, 2002, now issued as U.S. Pat. No. 7,596,474, U.S. patent application Ser. No. 09/995,222, filed on Nov. 27, 2001, now issued as U.S. Pat. No. 7,519,518, and U.S. patent application Ser. No. 09/675,778, filed on Sep. 29, 2000, now issued as U.S. Pat. No. 7,623,991, the disclosures of which are each hereby incorporated by reference herein in their entirety.

An automatic technique for combining the one or more systems may be desirable such that the combination of the systems together may be modeled and accordingly represented in terms of combined physical quantities and equations. It may also be desirable for the automatic technique to provide for selectively solving for one or more variables associated with the combined system and/or for solving the variables associated with one or more of the individual systems.

It may be desirable in certain embodiments to model the physical quantities of a particular system using different sets of equations to represent the model. This can allow for different techniques to be utilized to solve the system of equations associated with a singular or combined system. For example, different forms of equations may be determined to be more desirable, such as linear or non-linear equations, because they provide expedient and efficient solutions. It is contemplated that in certain embodiments, systems of partial differential equations having multiple geometries can be desirable. Partial differential equations can provide an efficient and flexible arrangement for defining various couplings between the partial differential equations within a single geometry, as well as, between different geometries.

It is contemplated that computer system(s) on which modeling systems operate, such as the ones described herein, can include networked computers or processors. In certain embodiments, processors may be operating directly on the modeling system user's computer and in other embodiments, a processor may be operating remotely. For example, a user may provide various input parameters at one computer or terminal located at a certain location. Those parameters may be processed locally on the one computer or they may be transferred over a local area network or a wide area network, to another processor, located elsewhere (e.g., another room, another building, another city) that is configured to process the input parameters. The second processor may be associated with a server connected to the Internet (or other network) or the second processor can be several processors connected to the Internet (or other network), each handling select function(s) for developing and solving a problem on the modeling system. Any of the processes or steps associated with the modeling system that are described herein can be performed by any one of the processors. It is further contemplated that the results of the processing by the one or more processors can then be assembled at yet another server or processor. It is also contemplated that the results may be assembled back at the terminal or computer where the user is situated. The terminal or computer where the user is situated can then display the solution of the modeling system to the user via a display (e.g., a transient display) or in hard copy form (e.g., via a printer). Alternatively, the solution may be stored in a memory associated with the terminal or computer, or the solution may be stored on another server that the user may access to obtain the solution from the modeling system.

It is contemplated that in certain embodiments a product or system may be in the development or feasibility stage where it is being designed or analyzed. Such a product or system may be the subject of a multiphysics modeling system which can be used to assess the product or system in complex environment(s) involving several physical quantities or parameters. It may also be desirable to solve complex multiphysics problems associated with various products or systems by systematically varying parametric and geometric features in a computer-based design system. Other desirable features may include, for example, to have a computer-based system for solving complex multiphysics problems in which the settings for the physical properties and boundary conditions located in a memory and used to form multiphysics models and/or solve multiphysics problems can be accessed directly from the design system, such as through an interface between the design system and the multiphysics modeling system or an interface within one of the design system or the multiphysics modeling system. It is contemplated that the interface may be virtual or reside in a permanent memory. It is also contemplated the interface may at least partially include physical hardware components that may or may not also include software components for allowing useful interactions between the design system and the multiphysics modeling system. It is further contemplated that it may be desirable to have a modeling system having logical relationships established between various model components using a model tree that includes a plurality of nodes with branch relationships between the nodes.

Referring now to FIG. 1, an exemplary aspect of a computer system is illustrated. The computer system 10 includes a data storage system 12 connected to host systems 14 a-14 n through communication medium 18. In this embodiment of the computer system 10, the N hosts 14 a-14 n may access the data storage system 12, for example, in performing input/output (PO) operations. The communication medium 18 may be any one of a variety of networks or other type of communication connections as known to those skilled in the art. For example, the communication medium 18 may be the Internet, an intranet, or other network connection by which the host systems 14 a-14 n may access and communicate with the data storage system 12, and may also communicate with others included in the computer system 10.

Each of the host systems 14 a-14 n and the data storage system 12 included in the computer system 10 may be connected to the communication medium 18 by any one of a variety of connections as may be provided and supported in accordance with the type of communication medium 18. The processors included in the host computer systems 14 a-14 n and the data manager system 16 may be any one of a variety of commercially available single or multi-processor system, such as an Intel-based processor, IBM mainframe or other type of commercially available processor able to support incoming traffic in accordance with each particular embodiment and application.

It should be noted that the particulars of the hardware and software included in each of the host systems 14 a-14 n, as well as those components that may be included in the data storage system 12 are described herein in more detail, and may vary with each particular embodiment. Each of the host computers 14 a-14 n, as well as the data storage system 12, may all be located at the same physical site, or, alternatively, may also be located in different physical locations. Examples of the communication medium that may be used to provide the different types of connections between the host computer systems, the data manager system, and the data storage system of the computer system 10 may use a variety of different communication protocols such as SCSI, ESCON, or Fiber Channel. Some or all of the connections by which the hosts, data manager system 16 and data storage system 12 may be connected to the communication medium 18 may pass through other communication devices, such as a Connectrix or other switching equipment that may exist such as a phone line, a repeater, a multiplexer or even a satellite.

Each of the host computer systems may perform different types of data operations, such as storing and retrieving data files used in connection with an application executing on one or more of the host computer systems. For example, a computer program may be executing on the host computer 14 a and store and retrieve data from the data storage system 12. The data storage system 12 may include any number of a variety of different data storage devices, such as disks, tapes, and the like in accordance with each implementation. As will be described in following paragraphs, software may reside and be executing on any one of the host computer systems 14 a-14 n. Data may be stored locally on the host system executing software, as well as remotely in the data storage system 12 or on another host computer system. Similarly, depending on the configuration of each computer system 10, software as described herein may be stored and executed on one of the host computer systems and accessed remotely by a user on another computer system using local data. A variety of different system configurations and variations are possible then as will be described in connection with the embodiment of the computer system 10 of FIG. 1 and should not be construed as a limitation of the techniques described elsewhere herein.

Referring now to FIG. 2, an exemplary aspect of the software 19 is illustrated that may reside in one of the host computer systems such as whose computer system 14 a-14 n. The software of computer system 14 a of FIG. 2 may include a User Interface module 20 that communicates with the Modeling and Simulation module 22. The software further includes a Data Storage and Retrieval module 24 which communicates with the Modeling and Simulation module 22 for performing tasks in connection with data storage and retrieval. The Data Storage and Retrieval module 24 may retrieve data files, for example, that may be stored in Libraries 26 as well as perform data operations in connection with User Data Files 28.

It should be noted that certain embodiments may include other software components other than what is described and functionally represented in the software modules 19 of FIG. 2. In the embodiment shown in FIG. 2, both the Libraries and the User Data Files are shown as being stored locally within the host computer system. It should also be noted that the Libraries and/or User Data Files, as well as copies of these, may be stored in another host computer system as well as in the Data Storage System 12 of the computer system 10. However, for simplicity and explanation in paragraphs that follow, it is assumed that the software may reside on a single host computer system, such as 14 a, with additional backups, for example, of the User Data Files and Libraries, in the Data Storage System 12.

In certain embodiments, portions of the software 19, such as the user interface 20, the Modeling and Simulation module 22, Data Storage and Retrieval module, and Libraries 26 may be included in combination in a commercially available software package. These components may operate on one of the host systems 14 a-14 n running Matlab V5.0, as well as one of Windows 95 or 98, Windows NT, Windows XP, Windows Vista, Windows 7, Mac OS X, Unix, or Linux operating systems. One embodiment of the software 19 may be implemented using MATLAB5.3 running on one of Windows 95, Windows NT, Unix or Linux operating systems.

The User Interface module 20 as will be described in more paragraphs that follow, may display user interface screens in connection with obtaining data used in performing modeling, simulation, and/or other problem solving for one or more systems under consideration. These one or more systems may be modeled and/or simulated by the Modeling and Simulation module 22. Data gathered such as in connection with the User Interface 20 and used by the Modeling and Simulation module 22 may be forwarded to the Data Storage and Retrieval module 24 where user-entered data, for example, may be stored in User Data Files 28. Additionally, other data and information may be obtained from the Libraries 26 as needed by the Modeling and Simulation module or in connection with the User Interface 20. In this particular example, the software in the modules may be written in any one of a variety of computer programming languages such as C, C++, Java or any combination of these or other commercially available programming languages. For example, one embodiment includes software written in MATLAB 5.3 and C. C routines may be invoked using the external function interface of MATLAB.

Additionally, various data files such as User Data Files 28 and the Libraries 26 may be stored in any one of a variety of data file formats in connection with a file system that may be used in the host computer system, for example, or in the Data Storage System 12. An embodiment may use any one of a variety of database packages in connection with the storage and retrieval of data. The User Data files 28 may also be used in connection with other software simulation and modeling packages. For example, the User Data files 28 may be stored in a format that may also be used directly or indirectly as an input to any one of a variety of other modeling packages, such as Matlab. In particular, an embodiment may provide for importing and exporting data between this system and another system, such as Matlab, for example. The precise format of the data may vary in accordance with each particular embodiment as well as the additional functionalities included therein.

As described in more detail elsewhere herein and in U.S. patent application Ser. No. 10/042,936, filed on Jan. 9, 2002, now issued as U.S. Pat. No. 7,596,474, U.S. patent application Ser. No. 09/995,222, filed on Nov. 27, 2001, now issued as U.S. Pat. No. 7,519,518, and U.S. patent application Ser. No. 09/675,778, filed on Sep. 29, 2000, now issued as U.S. Pat. No. 7,623,991, the disclosures of which are each hereby incorporated by reference herein in their entirety, various techniques may be used for combining application modes modeling different systems. Properties of these application modes represented by partial differential equations (PDEs) may be automatically combined to form PDEs describing these quantities in a combined system or representation. The combined PDEs when displayed, for example, in a “coefficient view” may be modified and further used as input to a finite element solver. It should be noted that the differential equations may be provided to the finite element solver either independently, describing a single system, or as a combined system of PDEs.

The software 19 provides the ability to combine application modes that model physical properties through one or more graphical user interfaces (GUIs) in which the user selects one or more application modes from a list. When a plurality of application modes are combined, this may be referred to as a multiphysics model. In addition to the application mode names, the variable names for the physical quantities may be selected through a GUI. Application modes may have different meanings depending on a “submode” setting. This is described in more detail elsewhere herein.

The physical properties that are used to model the physical quantities in a system under examination in connection with the software 19 may be defined using a GUI in which the physical properties may be described as numerical values. These physical properties may also be defined as mathematical expressions including one or more numerical values, space coordinates, time coordinates and the actual physical quantities. The physical properties may apply to some parts of a geometrical domain, and the physical quantity itself can also be disabled in the other parts of the geometrical domain. A geometrical domain or “domain” may be partitioned into disjoint subdomains. The mathematical union of these subdomains forms the geometrical domain or “domain”. The complete boundary of a domain may also be divided into sections referred to as “boundaries”. Adjacent subdomains may have common boundaries referred to as “borders”. The complete boundary is the mathematical union of all the boundaries including, for example, subdomain borders. For example, in certain embodiments, the geometrical domain may be one-dimensional, two-dimensional or three dimensional in the GUI. However, as described in more detail elsewhere herein, the PDE solution solvers may be able to handle any space dimension. Through the use of GUIs in one implementation, the physical properties on the boundary of the domain may be specified and used to derive the boundary conditions of the PDEs.

Additional function included in the software 19, such as in the Modeling and Simulation module, may provide for automatically deriving the combined PDE's and boundary conditions of the multiphysics modeling system. This technique merges the PDEs of the plurality of systems, and may perform symbolic differentiation of the PDEs, and produce a single system of combined PDEs.

The combined PDEs may be modified before producing a solution. In certain embodiments, this may be performed using a dialog box included in a GUI displaying the combined PDEs in a “coefficient view”. When the derived PDEs are modified in this way, the edit fields for the corresponding physical properties become “locked”. The properties may subsequently be unlocked in certain embodiments by an explicit user action.

It should be noted that certain embodiments may include functionality for modeling any one or more of many engineering and scientific disciplines. These may include, for example, acoustics, chemical reactions, diffusion, electromagnetics, fluid dynamics, general physics, geophysics, heat transfer, porous media flow, quantum mechanics, semiconductor devices, structural mechanics, wave propagation, and the like. Some models may involve more than one of the foregoing systems and rather may require representing or modeling a combination of the foregoing. The techniques that are described herein may be used in connection with one or more systems of PDEs. In certain embodiments described herein, these PDEs may be represented in general and/or coefficient form. The coefficient form may be more suitable in connection with linear or almost linear problems, while the general form may be better suited for use in connection with non-linear problems. The system(s) being modeled may have an associated submode, for example, such as stationary or time dependent, linear or non-linear, scalar or multi-component. Certain embodiments may also include the option of performing, for example, eigenvalue or eigenfrequency analysis. In the embodiment described herein, a Finite Element Method (FEM) may be used to solve for the PDEs together with, for example, adaptive meshing and a choice of a one or more different numerical solvers.

In certain embodiments, a finite element mesh may include simplices forming a representation of the geometrical domain. Each simplex belongs to a unique subdomain, and the union of the simplices forms an approximation of the geometrical domain. The boundary of the domain may also be represented by simplices of the dimensions 0, 1, and 2, for geometrical dimensions 1, 2, and 3, respectively. The finite element mesh may be formed by using a Delanunay technique, for example, as described in “Delanunay Triangulation and Meshing”, by P.-L. George, and H. Bourouchaki, Hermes, Paris, 1998. Generally, this technique may be used to divide the geometrical domain into small partitions. For example, for a 1-dimensional domain, the partitions may be intervals along the x-axis. For a 2-dimensional square domain, the domain may be partitioned into triangles or quadrilaterals. For a 3-dimensional domain, the domain may be partitioned into tetrahedrons, blocks or other shapes.

It should be noted that a mesh representing a geometry may also be created by an outside or external application and may subsequently be imported for use into the system(s) and embodiment(s) described in the present disclosure.

The initial value of the solution process may be given as numerical values, or expressions that may include numerical values, space coordinates, time coordinates and the actual physical quantities. The initial value(s) may also include physical quantities previously determined.

The solution of the PDEs may be determined for any subset of the physical properties and their related quantities. Further, any subset not solved for may be treated as initial values to the system of PDEs.

Referring now to FIG. 3, an exemplary aspect of a user interface or GUI 30 is illustrated that may be used in connection with specifying a multiphysics modeling system of more than one system to be combined. In this example, each system to be combined may correspond to an application mode. Through the use of the GUI 30, the application modes that are to be used in this combined multiphysics modeling system may be specified. Each application mode models physical quantities in terms of PDEs. The physical quantities may be represented either directly as the dependent variables in the PDE, or by a relation between the dependent variable and the variable representing the physical quantity. The PDEs in this embodiment may be generally “hidden” from the user through the use of the GUIs. When several application modes are combined into one single model or system, it may be referred to as a multiphysics model.

The list of application modes 32 is the list of possible application modes from which a user may select in accordance with the user choice of space dimension indicated the buttons 56 in the left-hand top of the GUI 30. To add application modes to a multiphysics model, the user selects application modes from the left-most list box 32 and may specify that these application modes are to be included in a multiphysics model, for example, selecting the button 33 a. After selection, this application mode is added to the list 58 on the right hand side of the GUI 30. Application modes may also be removed from the list by selecting button 33 b. Before adding an application mode, the user may edit its name 36 and names of the variables 38 representing the physical quantities that may be solved for, for example, resulting in the new name 44 and new name of the variable 46.

Each application mode in the multiphysics model is given a unique name that may be used to identify the origin of the variables in the multiphysics model. The example shown in the GUI 30 is for an application mode “Heat Transfer” in the list 32. When selected using button 33 a, the application mode appears on list 58. The user may edit the application mode name, for example, changing it from that included in display 36 to the corresponding name of display item 44. Similarly, the dependent variable name may be modified from that shown in item 38 to the item 46. In this example, only one variable is associated with the Heat Transfer application mode. For an application mode including more than one physical quantity, the user may enter all the names of the physical quantities as space-separated entries in the Dependent variables edit field 46.

There are also application modes that directly correspond to PDEs. In these modes, the quantities are represented by the dependent variables. Each of these application modes may have more than one dependent variable. The number of dependent variables and the dimension of system of PDEs may be determined by entering one or more corresponding space-separated variable names.

On the right-hand side of the multiphysics GUI 30, a solver type and solution form may be selected. The solver type may be specified in the item 40, for example, as one of stationary, time-dependent, and the like. Similarly, the solution form may be specified in item 42, for example as “coefficient” or “general” form. These refer to the form of the PDE for which the solution is derived and are described in more detail elsewhere herein. The solver types and solution forms may vary in accordance with the application modes of the multiphysics model. In the list box 58, all the application modes that have been added to the model appear. A user may select any of the model's application modes and change its submode 48. Generally, a submode may relate to the manner in which equations are derived or differentiated, for example, with respect to what variables differentiation may be performed.

In this example, the standard submode is specified at element 48. Additionally, an application mode may include other associated submodes, for example, such as, a wave-extension submode that extends a standard time-dependent equation to a wave equation using the second derivative of the standard equation with respect to time. Selecting OK using button 31 a saves the updated multiphysics model with all the added application modes and closes the GUI 30. In contrast, selecting Cancel using button 31 b closes the GUI and discards any changes. Referring to FIG. 2, when the OK button 31 a is selected, the data may be communicated from the GUI 20 to the Modeling and Simulation Module 22 and subsequently to the Data Storage and Retrieval Module 24 for storage in the User Data Files 28.

The foregoing screen display, such as GUI 30, may be displayed by and included as a portion of the software of the User Interface Module 20 of the software 19. It should be noted that certain embodiments may include different types of application modes. In one embodiment, application modes may be classified as one of user defined or predefined; A predefined application mode may be one for which functionality is included in the libraries 26 as may be available from a software vendor. In other words, a software vendor may supply libraries including defined systems of PDEs, GUIs and the like for a particular type of system, such as heat transfer. Additionally, an embodiment may include support to provide for user-defined models or application modes for which a user may specify the PDEs, the quantities being modeled, and the like. Subsequently, a user-defined model may be saved in a user defined library, for example, included in the user defined data files 28. Definitions and other data files associated with a user-defined model may be stored in any one of a variety of data formats, for example, similar to those of the libraries 26 that may be included in an implementation by a software vendor. The format and function may vary in accordance with each embodiment.

In certain embodiments, a user may define and add a user-defined application mode by adding functions in MATLAB format for transforming the physical properties on subdomains, boundaries, and initial conditions. The user may specify a first function, equ_compute, for transforming physical quantities to PDE coefficients, a second function, bnd_compute, for transforming the physical properties on the boundaries to boundary conditions, and a third function, init_compute, for transforming the physical properties in the initial condition. More detail on user defined application modes is described elsewhere herein.

Referring now to FIG. 4, an exemplary aspect of an screen display of the physical property specification GUI 60 is illustrated for the heat transfer application mode. It is contemplated that each application mode may have a specifically designed GUI display in which the physical properties associated with that application mode may be specified. The list 62 in the left of the GUI 60 includes one or more geometrical domains to which the physical properties may apply. These may also be referred to as subdomains. The user may select one or several subdomains from the list 62, for example, using a mouse, keyboard or other selection device. If a single subdomain is selected, entering a new name in the edit field Name 62 a may change the name. If the user selects multiple subdomains, the properties that are specified apply to all the selected subdomains. The “on-top” check box 64 a makes the boundary condition GUI “float” on top of the view of the geometrical domain also. In other words, the corresponding dialog box “floats” on top of other items that may be displayed on the screen in connection with the GUI.

In certain embodiments, if the properties of the currently selected subdomains differ, the edit fields for the properties may be “locked” for no editing. One may unlock the subdomains by explicitly checking the Unlock check box 64 a. The properties from the first selected subdomain may be copied to all the selected subdomains.

It should be noted that in certain embodiments, selecting several subdomains with different physical properties may also cause locking. Checking “unlocking” may then result in the properties in the first selected subdomain being copied to the other subdomains.

The physical properties of the subdomains are specified in the list 64. As previously described, these properties may be specified as numerical values, or also as symbolic expressions in terms of the space coordinates, the physical quantities and their space derivatives, and the time. Additionally, a name of a procedure to compute a value of the property may also be specified by entering the name and any parameters that may be included in the procedure. In certain embodiments, the procedure may be written, for example, in C, Fortran, or Matlab. The particular language of implementation may vary in accordance with each particular embodiment and the calling standards and conventions included therein.

A user may also disable the physical quantities of an application mode in a subdomain entirely by un-checking the “Active in this Subdomain” checkbox 66. This removes the properties in 64 from the application in the selected subdomain(s). Also the physical quantities in this application mode are disabled in the selected subdomain(s).

Referring now to FIG. 5, an exemplary aspect of a screen display of a GUI 70 is illustrated, which is a physical property boundary specification GUI for the heat transfer application mode. The list 72 in the left portion of the GUI 70 includes geometrical boundaries where the physical properties may apply. Only the boundaries that form the outer boundary with respect to the active subdomains are included in the list. As described elsewhere herein, those subdomains that are “active” may be specified in the GUI 60 for physical properties.

Boundaries that are entirely inside the subdomain or between two subdomains are also not shown unless the “Enable borders” check box 72 a is selected. A user may select one or several boundaries from the list 72. If the user selects a single boundary, the user can change its name by entering a new name in the Name edit field 72 b. If the user selects multiple boundaries, the properties that the user specifies, as in list 74, apply to all the selected boundaries. If the properties on the currently selected boundaries differ, the edit field 72 b for the properties is locked. One may unlock the subdomains by explicitly checking the “Unlock” check box 74 a. The properties from the first selected boundary are then copied to all the selected boundaries.

In certain embodiments, selecting several boundaries with different physical properties may also cause locking. Checking “unlock” may then result in the properties in the first selected boundary being copied to the other boundaries.

The physical properties of the geometrical boundaries are specified in the list 74 in the right hand portion of the GUI 70. These properties have values that may be specified as numerical values, or symbolic expressions in terms of the space coordinates, the physical quantities and their space derivatives from any application modes added by using the previous section, and the time. Additionally, the name of a procedure to determine the value of the property may also be specified in a manner similar to as described elsewhere herein.

It should be noted that a portion of the different GUIs displayed may be similar, for example, such as the “on top” check box 74 b that is similar in function to 64 a as described elsewhere herein.

Referring now to FIG. 6, an exemplary aspect of a screen display is illustrated that may be used in connection with modifying the PDEs in a “coefficient view”. Using this interface 80 of FIG. 6, this may be used in connection with modifying the boundary conditions in coefficient view as associated with the combined system of PDEs. It should be noted that other embodiments may also include a similar screen display and interface to allow for modification of PDEs of each individual application mode or system being modeled. Additionally, an embodiment may also include a similar screen display for modifying a system in general form rather than coefficient form as shown in the display 80 of FIG. 6.

The GUI 80 may be displayed in connection with modifying the boundary conditions associated with a coefficient. For example, in the GUI 80, the boundaries 1 and 3 have been selected as associated with the coefficient tab “q” 82 a corresponding to the coefficient appearing in the PDE at position 84 a. The list 90 on the right hand side of the GUI 80 includes the boundary conditions associated with the active “q” coefficient. A user may modify the conditions associated with the currently active coefficient, such as “q”. Any one of the tabbed coefficients, such as 82 a-82 d may be made active, for example, by selecting the tab, such as with a mouse or other selection device. This causes the right hand portion 90 of the GUI 80 to be updated with corresponding values for the currently active coefficient. The values may be modified by editing the fields of 90 and selecting the OK button 92 a, or the apply button 92 c. The modification may be cancelled, as by selecting the cancel operation button 92 b. A boundary number that is selected on list 88 may be changed to have a symbolic name, as may be specified in field 96. The values indicated in 90 are set accordingly for the selected boundaries 88. The on-top check box 94, and other features of GUI 80, are similar to those appearing in other GUIs and described in more detail elsewhere herein.

It should be noted that the PDE coefficient and boundary conditions associated with the combined system of PDEs for the various application modes selected may be stored in a data structure that is described in more detail elsewhere herein. Subsequently, if these coefficient and boundary conditions are modified, for example, using the GUI 80 of FIG. 6, the corresponding data structure field(s) may be updated accordingly. As described elsewhere herein and in U.S. patent application Ser. No. 10/042,936, filed on Jan. 9, 2002, now issued as U.S. Pat. No. 7,596,474, U.S. patent application Ser. No. 09/995,222, filed on Nov. 27, 2001, now issued as U.S. Pat. No. 7,519,518, and U.S. patent application Ser. No. 09/675,778, filed on Sep. 29, 2000, now issued as U.S. Pat. No. 7,623,991, the combined system of PDEs and associated boundary condition fields may be updated.

It should also be noted that the dialog for modifying the boundary conditions in coefficient view of a system of three variables may be viewed in the example GUI 80 of FIG. 6. If the system to be solved is in general form, the coefficient view dialog box may also include symbolic derivatives of the general form coefficients with respect to the physical quantities or solution components and their derivatives according to FIG. 10. As described in more detail elsewhere herein, the derivatives may be used for the solution of nonlinear stationary and time-dependent problems.

In certain embodiments, when the coefficients in coefficient view are changed for a subdomain or a boundary, the “Unlock check-box” in the corresponding application modes for that subdomain or boundary dialog box is enabled, as previously described in connection with GUI 70 of FIG. 5. In certain embodiments, in order to disable the change in coefficient view, a user may remove the checkmark as may be displayed in the Unlock check box on the subdomain or boundary in the application mode, for example, as described in connection, respectively, with GUIs 60 and 70.

Using the GUIs 60 and 70 for, respectively, physical properties for subdomains and boundaries, as well as possible modifications specified as with GUI 80, the Modeling and Simulation Module 22 may create, initialize, and possibly modify the data structure 250 of FIG. 6A.

Referring now to FIG. 6A, shown is an example of a representation of the data structure that may be included in an embodiment in connection with storing data in connection with the PDEs selected and combined. The data in the data structure 250 may include data used in connection with the multiphysics model.

The data structure 250 includes the following fields:

Data field Description fem.mesh Finite element mesh fem.appl{i} Application mode I fem.appl{i}.dim Dependent variable name fem.appl{i}.equ Domain physical data fem.appl{i}.bnd Boundary physical data fem.appl{i}.submode Text string containing submode setting fem.appl{i}.border Border on or off fem.appl{i}.usage Matrix of subdomain usage fem.dim Multiphysics dependent variable names fem.equ PDE coefficients fem.bnd Boundary conditions fem.border Vector of border on or off fem.usage Multiphysics subdomain usage matrix fem.init Initial value fem.sol Finite element solution

The field fem.mesh 252 includes the finite element discretization. The mesh partitions the geometrical domain into subdomains and boundaries. Data stored in this field may be created from an analyzed geometry. A mesh structure representing a geometry may also be created by an outside or external application and may subsequently be imported to use in this system in this embodiment. To obtain good numerical results in the solution to a particular multiphysics problem, the mesh may have certain specific characteristics available in connection with an externally provided mesh, such as by a MATLAB routine. In instances such as these, a mesh may be imported from a compatible external source. Support may vary with embodiment as to what external interfaces are supported and what external formats of meshes may be compatible for use with a particular implementation. For example, a mesh structure may be compatible for use with an embodiment such as a mesh structure produced by the product TetMesh by Simulog, and HyperMesh by Altair Engineering.

In one embodiment, a geometry is used in generating a mesh structure. In other words, in an embodiment that includes functionality to define and create a mesh as an alternative to obtaining a mesh, for example, from an external compatible software product, a geometry definition may be used in generating a mesh structure. What will now be described is a function that may be included in an embodiment. An embodiment may include any one or more of a variety of alternatives to represent a geometry of a PDE problem to be solved. One technique includes defining a geometry in accordance with a predefined file format, predefined formatted object, and the like. It should be noted that an embodiment may include the option of importing a predefined file format or specifying a function for describing the geometry.

It should be noted that the predefined file format may include differences in accordance with the varying dimensions that may be supported by an embodiment.

An embodiment may include a function or routine definition for returning information about a geometry represented in accordance with a predefined file format. This routine may be included in an implementation, or, may also be defined by a user. In other words, an implementation may include support allowing a user to provide an interface function in accordance with a predefined template or API, such as particular input and output parameters and function return values. Such a routine may be used as an interface function, for example, to obtain geometry information in which a geometry may be represented in any one of a variety of predefined file formats, data structure formats, and the like.

The fem.mesh structure may represent a finite element mesh that is partitioning a geometrical domain into simplices. In one embodiment, minimal regions may be divided into elements and boundaries may also be broken up into boundary elements. In one embodiment of the mesh structure, the mesh may be represented by fields of data, two of which are optional. The five fields are: the node point matrix (p), the boundary element matrix (e), the element matrix (t), the vertex matrix (v) and the equivalence matrix (equiv), in which v and equiv may be optional. The matrix p includes the node point coordinates of the mesh. The matrix e may include information to assemble boundary conditions on δΩ, such as node points of boundary elements, parameter values on boundary elements, geometry boundary numbers, and left and right subdomain numbers. The matrix t includes information needed to assemble the PDE on the domain Ω. It includes the node points of the finite element mesh, and the subdomain number of each element. The matrix v includes information to recreate geometric vertices. The equiv matrix includes information on equivalent boundary elements on equivalent boundaries. It should be noted that contents and of the data structure may vary with dimension of the domain being represented. For example, in connection with a 2-dimensional domain, the node point matrix p may include x and y coordinates as the first and second rows of the matrix. The boundary element matrix e may include first and second rows that include indices of the starting and ending point, third and fourth rows including the starting and ending parameter values, a fifth row including the boundary segment number, and sixth and seventh rows including left and right hand side subdomain numbers. The element matrix t may include in the first three rows indices of the corner points, given in counterclockwise order, and a fourth row including a subdomain number. The vertex matrix v may have a first row including indices into p for vertices. For isolated vertices, the second row may also include the number of the subdomain that includes the vertex. For other vertices, the second row may be padded. The field v may not be used during assembly, but rather have another use when the mesh structure, for example, may be used in connection with other operations or data representations. The equivalence matrix equiv may include first and second rows of indices into the columns in e for equivalent boundary elements. The third and fourth row may include a 1 and 2, or a 2 and 1 depending on the permutation of the boundaries relative to each other.

As another example of the mesh structure, consider one that may be used in connection with a 1-dimensional structure being represented. The node matrix p may include x coordinates of the node points in the mesh in the first row. In the boundary element matrix e, the first row may include indicates of the boundary point, the second row may include the boundary segment number, and the third and fourth rows may include left and right hand side subdomain numbers. In the element matrix e, the first two rows include indices to the corner points, given from left to right, and the third row includes the subdomain number. In a 1-dimensional domain, there is no vertex matrix since vertices are exactly equivalent to the boundaries. In the equivalence matrix equiv, the first and second rows include indices into the columns in e for equivalent boundaries. The third row is padded with ones.

In one embodiment, the fern structure may additionally include a fem.equiv field indicating boundaries that should be equivalent with respect to elements and node points, e.g., for periodic boundary conditions. One implementation of fem.equiv includes a first row with master boundary indices and a second row with slave boundary indices. The mesh has the same number of node points for the boundaries listed in the same column. The points are placed at equal arc-length from the starting point of the equivalent boundaries. If a negative number is used in row two, the slave boundary may be generated by following the master boundary from end point to start point. A master boundary may not be a slave boundary in another column.

Following is a summary of the Delaunay triangulation method in connection with forming a 2-dimensional mesh structure:

1. Enclose geometry in a bounding box

2. Put node points on the boundaries following HMAX

3. Perform Delaunay triangulation of the node points on the boundaries and the vertices of the box. Use the properties MINIT/ON and BOX/ON to see the output of this step.

4. Insert node points into center of circumscribed circles of large elements and update Delaunay triangulation until HMAX is achieved.

5. Check that the Delaunay triangulation respects the boundaries and enforce respected boundaries.

6. Remove bounding box.

7. Improve mesh quality.

-   -   in which HMAX refers to the maximum element size; BOX and MINIT         and other properties that may be used in one embodiment are         summarized below:

Property 1-D 2-D Value Default Description Box X on/off off preserve bounding box Hcurve X numeric ⅓ curvature mesh size Hexr X X string maximum mesh size Hgrad X X numeric  1.3 element growth rate Hmax X X numeric estimate maximum or cell element array size Hmesh X X numeric maximum element size given per point or element on an input mesh Hnum X X numeric, number of cell elements array Hpnt X numeric, number of cell resolution array points Minit X on/off off boundary triangulation jiggle X off/mean mean call mesh min/on smoothing routine Jiggleiter X numeric 10 maximum iterations out X X values mesh output variables

The foregoing properties may be used in connection with forming a mesh structure. The Box and Minit properties are related to the way the mesh method works. By turning the box property “on”, one may obtain an estimate of how the mesh generation technique may work within the bounding box. By turning on minit, the initial triangulation of the boundaries may be viewed, for example, in connection with step 3 above.

Hcurve is a scalar numeric value relating the mesh size to the curvature of the geometry or mesh boundaries. The radius of the curvature is multiplied by the hcurve factor to obtain the mesh size along the boundary. Hexpr is a string including an expression of x and y giving the size of the elements at different coordinates using the mesh structure. Hmax controls the size of the elements in the mesh. Hmax may either be a global value, or a cell array. The syntax of the cell array varies in accordance with 1-D and 2-D. For 2-D, the first entry in the cell includes a global Hmax, the second entry is a matrix with two rows where the first row includes point indices and the second row includes Hmax and corresponding points. The third entry includes indices to edge segments and corresponding Hmax, and the fourth entry includes indices to subdomains and corresponding Hmax. For a 1-D the first entry in the cell includes a global Hmax, the second entry is a matrix with two rows where the first row includes point indices, and the second row includes Hmax in the corresponding points. The third entry includes indices to the subdomains and corresponding Hmax.

Hmesh is a vector with one entry for every node or element in the mesh given in the mesh structure. Hnum controls the approximate number of elements in the mesh. Depending on other properties, the number of elements specified by Hnum may be exceeded, but at least as many elements specified are generated. Hnum may be either a global numeric value or a cell array. Syntax of the cell array varies with 1-D or 2-D. For 2-D, the first entry in the cell includes a global Hnum, the second entry is a matrix with two rows where the first row include edge indices and the second row includes Hnum on the corresponding edges. For 1-D, the first entry in the cell includes a global Hnum, the second entry is a matrix with two rows where the first row includes subdomain indices and the second row includes Hnum on the corresponding subdomain.

The Hpnt property controls the number of points placed on each edge to resolve the mesh. Additional points may be placed as needed in accordance with the curvature and distances. It is either a number for all edges, or a cell. If it is a cell array, the first entry applies to all edges and the second entry is a matrix with two rows where the first row includes edge indices and the second row includes Hpnt on that edge.

The Jiggle property may be used to control whether “jiggling” of the mesh may be attempted, for example, in using a smoothing technique. This may be performed until the minimum or mean of the quality of elements decreases by setting jiggle accordingly to min or mean. Jiggleiter may be used to specify a maximum number of iterations.

It should be noted that the foregoing properties may be included as parameters to an API for forming a mesh structure, for example, using the Delaunay triangulation method. Other techniques may also be used and the exact parameters in an embodiment using an API may also vary. Additionally, other embodiments may also include other representations of the mesh structure that may vary in accordance with dimension of the geometry.

Referring back to other fields of the fern structure in one embodiment, each application mode has a separate fem.appl {i} field 254, referred to as appl{i}. The index i in the appl vector runs over the set of application modes that have been selected, for example, in connection with FIG. 3. In this embodiment, corresponding to each appl{i} for each selected application mode are five subfields denoted 254 a-254 e. The appl {i}.dim field 254 a includes the names of the dependent variables or physical quantities in application mode i. The appl{i}.equ field 254 b includes the physical properties associated with subdomain data, for example as described in connection with FIG. 4. The field appl{i}.bnd 254 c includes data describing the physical properties associated with boundary data, for example as described in connection with FIG. 5, for application mode i. The field border 254 d is a flag that controls if boundary conditions on inner boundaries are to be considered, and, for example, corresponds to the “Enable Borders check box” as described in connection with the GUI of FIG. 5. There is one border flag for each application mode. The field usage 254 e corresponds to the “Activate in this Subdomain check box” as described in connection with the GUI of FIG. 4. In one embodiment, this may be implemented as a boolean vector, with one column for each geometrical subdomain. A logical value of “1” or true in an entry indicates that application mode i is active in the subdomain corresponding to that column. Fem.appl{i}.submode represents a corresponding submode setting, such as 48 of FIG. 3.

In one embodiment, the remaining fields in the data structure 250 may be associated with the combined application modes. The field fem.dim 256 includes the names of the dependent variables or physical quantities in all application modes. The fields fem.equ 258 and fem.bnd 260 correspond to the derived equations and boundary conditions for all the application modes. These fields may be used in connection with data from dialog boxes for PDE and Boundary conditions in coefficient view, such as those GUIs described in connection with FIG. 6. Similarly the field fem.border 262 may be implemented as a vector specifying borders for each variable of the variables in appl{i}.dim separately. The field fem.usage 254 e includes data associated with the activation of dependent variables in each geometrical subdomain. The variables in fem.dim 256 correspond to the rows of the fem.usage field 264, and the columns correspond to the geometrical subdomains. The field fem.init 266 includes the initial value for nonlinear and time dependent solvers, for example, as may be used in connection with solving for the PDEs. The field fem.sol 268 may include the solution to the combined system of PDEs using a solution or PDE solving technique, for example, as may be selected in accordance with the GUI of FIG. 7, other parameters included in the structure 250, and the type of PDE system being solved, such as whether the PDEs correspond to a linear or non-linear system, are in coefficient or general form, and the like. The field 270 indicates that other fields may be included in an embodiment in accordance with each implementation.

The equ fields 254 b may include several application mode dependent subfields with one list per physical property. Each list entries correspond to the subdomains of the problem. Each subfield may include a list of expression values representing the physical properties involved. For example, the heat transfer application mode includes the list: rho, C, k, Q, htrans, Text, Camb, Tambtrans, corresponding, respectively, to the density, heat capacity, coefficient of heat conduction, heat source, convective heat transfer coefficient, external temperature, user-defined constant, and transversal ambient temperature. This may be interpreted as a heat source of Q+htrans*(Text−T)+Camb*(Tambtranŝ4−T̂4) on a subdomain.

The usage fields 254 e and 264 describe the setting of the Active in this subdomain setting for each physical property (or dependent variable). The bnd fields 254 c include several application mode dependent subfields with one list per physical property. The list entries correspond to the boundaries of the subdomain. Each subfield contains a list of expression values for the physical quantities involved, e.g., the heat transfer application mode contains the list: q, h, Tinf, C, Tamb, and T, corresponding to the heat flux and heat transfer coefficient, external temperature, user-defined constant, ambient temperature, and temperature, respectively. An additional subfield, type, controls the basic type of the boundary condition and what physical properties are used on the boundary. For example, referring to the heat transfer application mode, the type may be one of T0, T, q, or q0. T0 indicates a zero temperature; T indicates that the temperature is specified in the field T; and q0 indicates a zero heat flux through that boundary, and q indicates a heat flux of q+h*(Tinf−T)+C*(Tamb̂4−T̂4) through that boundary.

The border fields 254 d and 262 indicate if the internal boundaries between subdomains are to be considered during the solution of the model. In one embodiment, the outer boundaries with respect to the active in this subdomain setting may be ignored. The equ fields 254 b and 258, and the bnd fields 254 c and 260 may further include an ind subfield. Each of the ind subfields may be implemented as a vector with length equal to the number of subdomains or boundaries. For each subdomain, the corresponding ind vector entry may indicate a domain group, or “0” for no group. For boundaries, each of the subfields bnd.ind may have the corresponding meaning for boundaries. When the ind field is not given, each subdomain or boundary forms a separate group.

Referring back to FIG. 6 in connection with GUI 80, fields in fem.equ 258 and fem.bnd 260 may be modified if they are specified as being applied to the combined PDE system and subsequently modified, for example, using the GUI 80.

Referring now to FIG. 7, an exemplary aspect of a screen display is illustrated that may be used in connection with solving the PDEs for any subset of physical quantities from any one or more application modes, or of the combined PDE system. The GUI 110 includes a left hand portion 114 displaying the one or more application modes selected with the current combined or multiphysics mode. The “show variables” box 114 a, if checked or activated, may modify the content displayed in area 114 to further include dependent variables in each of the associated application modes. In this instance, the physical quantities may be selected as well as a particular application mode with regard to solving for the combined system of PDEs in which the combined system includes those systems corresponding to the application modes in the area 114. The area 116 includes one or more various options that may be associated with solving for the PDEs. In this embodiment, the reference to “u” as included in the area 116 refers to all physical quantities for all application modes. Activating the field 116 b causes the updating of the appropriate data structure fields upon solving for the system of PDEs. Activating field 116 c uses interpolation in solving for the PDEs. This is described in more detail elsewhere herein.

The GUI 110 may be used in selecting what physical quantities to solve for in the System of PDEs. Selecting all application modes, such as by selection an highlighting application modes of area 114, solves for all physical quantities in the system of PDEs. Selecting a subset of the application modes solves for all the variables in these application modes. In one embodiment, checking the checkbox 114 a “Show variables” shows the actual variable names instead of the names of the application mode, and enables selection of these. The “Update u” button 116 a inserts the current solution (in fem.sol) into the initial conditions (in fem.init). The check-box “update u automatically” makes u automatically update the data structure fields fem.init with fem.sol each time a solution is computed, and the check-box “use interpolation” 116 c allows interpolation to be used when the current solution and the current discretization mesh are different. In one embodiment, the solution may be interpolated to the current discretization and inserted into fem.init. The use of interpolation, for example, is set forth in “Numerical Methods”, G. Dahlquist, {dot over (A)}. Björk, Prentice Hall, 1974, ISBN 0-13-627315. The “Use solution number” pop-up menu 116 d controls which solution to update fem.init with, for example, if there are several columns in fem.sol as may be for a time-dependent problem.

The values in the physical property fields of the application mode appl structure, for each of the “i” selected application modes, may be converted into PDEs. The formats of the PDEs formed for each specified application mode may be represented as in FIGS. 8 and 9.

Referring now to FIG. 8, shown is an example of an embodiment of formulae 140 describing a system of PDEs in coefficient form. Ω, formula 142, is for a bounded domain. The formulae 146, including 146 a-146 b δΩ, correspond to the boundary of the domain 142. n_(j) corresponds to the components of an outward unit normal.

The first equation 142 is satisfied inside the domain, and the second and third equations of 146 are both satisfied on the boundary of the domain. The second equation 146 a may be referred to as a generalized Neumann boundary condition, and the third equation 146 b may be referred to as a Dirichlet boundary condition.

The unknown solutions, such as those corresponding to the physical quantities, may be denoted by u_(k) in the formulae of 140. The unknown solutions may include one or more components. N denotes the number of solution components, or physical quantities. The solution is allowed to take complex values. λ_(m) is an unknown Lagrange multiplier. n_(j) is a component of the gradient of the solution. The coefficients included in the formulae 140 d_(a,l,k), c_(l,k,j,i), α_(l,k,j), γ_(i,j), β_(l,k,i), α_(l,k), f_(l), q_(l,k), g_(l), h_(m,l), and r _(m) may be complex-valued functions of the space, time, and the solution. The coefficients d_(a), c, α, g, β, a, and f may be functions of the gradient of u.

For a stationary system in coefficient form, for example as may be specified in FIG. 3, item 40, d_(a)=0. With respect to solution components, the coefficients d_(a), c, α, β, a, and q are N-by-N matrices, and γ, f and g are N vectors. The coefficient h is an M-by-N matrix, and r is an M vector, where 0<=M<=N and M is the number of constraints. With respect to space dimension, n, (or independent variables) the c coefficient is an n-by-n matrix, and the α, γ, and b coefficients are n vectors. The remaining coefficients may be scalars.

Referring to the indices of the formulae 140, i and j are space indices and k and l are component indices. Using the standard summation convention, i.e., there is an implicit summation over each index pair, i and j, and k and l, the formulae of FIG. 8 where the indices i and j run from 1 to n, the indices k and l run from 1 to N, and where the index m runs from 1 to M. n_(j) is the jth component of the outward normal vector.

Referring now to FIG. 9, shown is an example of an embodiment of a representation of formulae 150 describing a system of PDEs in general form. Here Ω 152 is a bounded domain, each δΩ, 154 a and 154 b of 154, is a boundary of the domain, and n_(j) is the outward unit normal. The unknown solution is denoted by u_(k) and may include one or more components. N denotes the number of physical quantities. The solution is allowed to take complex values. λ_(m), is an unknown Lagrange multiplier. The generalized Neumann condition, for example as expressed by 154 a, includes a source where the Lagrange multipliers λ_(m) are computed such that the Dirichlet conditions become satisfied. The coefficients Γ_(lj), F_(l), G_(lj), and R_(m), may be complex-valued functions of the space, time, the solution and its gradient. With respect to solution components the coefficients Γ, F and G are N vectors. The coefficient R is an M vector, where 0≦M≦N, and N is the number of constraints. The Γ coefficient is an n vector with respect to space dimension n. The rest of the coefficients are scalars with respect to space. Using j as a space index, and k and l as component indices in conjunction with implied standard summation convention, the general form 150 of FIG. 9 may be expressed where the index j runs from 1 to n, the indices k and l run from 1 to N, where the index m runs from 1 to M, and n_(j) is the jth component of the outward normal vector.

The application mode physical properties, for example, as described in connection with each selected application mode corresponding to an entry in the appl{i} structure, may be converted to the representation of PDEs in coefficient and/or general form. The combined PDEs may be represented in fields of the data structure 250, such as in the equ 258 and bnd 260 fields.

As described in more detail elsewhere herein, in one embodiment, the same syntactic rules may be used in determining coefficients for both PDEs, as may be represented in the equ field 258, and boundary conditions, as may be represented in the field 260. In other words, as summarized here and described further in more detail elsewhere herein are syntactic rules that may be used in forming coefficients for the PDEs. These rules may be used in forming coefficients for each system of PDEs associated with each application mode. These rules may also be used in connection with forming coefficients for the combined PDE or multiphysics system. The coefficients may be stored in nested lists. Each nested level of the lists may correspond to a nesting index position. For example, level 1 may corresponds to subdomain/boundary, level 2 may correspond to a solution component or physical quantity, and level 3 may correspond to the space coordinate. Level 4 may be a value level, where the actual expressions are stored. In connection with forming coefficients for each application mode selected, input data, as may be obtained in connection with previously described GUIs, may be converted to PDE format. Coefficients may be formed as part of this process. Data for each application mode may be stored in fields of the appl{i} data structure subfields dim, form, equ, bnd, and init.

For the combined or multiphysics, referring back to fields of the data structure 250 described in more detail elsewhere herein, the following list provides the position in the data structure 250 for the combined system of PDEs and boundary conditions with regard to those elements referenced, for example, in FIG. 8: d_(a): equ.da, c: equ.c, α: equ.al, γ: equ.ga, β: equ.be, a: equ.a,f: equ.f, q: bnd.q, g: bnd.g, h: bnd.h, r: bnd.r.

The general form coefficients, for example as described in connection with FIG. 9 and FIG. 11 in more detail elsewhere herein, Γ, F, G, and R may be stored in the equ.ga, equ.f, bnd.q, and bnd.r fields, respectively. A uniform format may be used for each of these coefficients. Subdomains and boundaries may be merged into groups where the expressions for the PDEs and boundary conditions are the same.

A subfield equ.ind of field 258 may be a vector with length equal to the number of subdomains. For each subdomain, the corresponding entry designates a subdomain group or 0 for no group. Similarly the field bnd.ind has the corresponding meaning for boundaries. When the ind field is not given, each subdomain or boundary form a separate group.

The data structure field fem.border 262 controls if assembly of boundary conditions are performed on borders. In one embodiment, this may be implemented as one or more boolean conditions each representing two states:“on” and off”. Setting fem.border 262 to “off” (default) turns off assembly on borders, and setting fem.border to “on” turns on assembly on borders. An embodiment may implement fem.border 262 as an array of text strings with either on or off conditions specified, or a vector of logical values. The length of the array or the vector may be equal to the number of dependent variables. A border for a given dependent variable has that variable activated by fem.usage on each side.

What will now be described are formal rules of one embodiment for determining coefficients at varying levels. Given a PDE or boundary coefficient P1 with L subdomains/boundary groups and N solution components, n space coordinates, with a varying number of levels, such as 1-4 having corresponding coefficient leveling notation P1-P4, respectively, the formal rules for coding the coefficients at varying levels in one embodiment may be represented as:

Level 1 (subdomain/boundary level): If P1 is a cell array then each element of P1 is a P2, otherwise P1 is a single P2. The number of P2s in P1 is either 1 or L.

Level 2 (solution component level): If P2 is a cell array then each element of P2 is a P3, otherwise P2 is a single P3. If P2 is a d_(a), c, α, β, a, or q coefficient the number of P3s in P2 is 1, N, N(N+1)/2, or N². If P2 is a γ, f, or g coefficient the number of P3s in P2 is 1 or N. If P2 is an h coefficient the number of P3s in P2 is 1 or MN, where M is an integer between 0 and N, representing the number of constraints. If P2 is an r coefficient the number of P3s in P2 is M.

Level 3 (space-coordinate level): If P3 is a cell array then each element of P3 is a P4, otherwise P3 is a single P4. If P3 is a c coefficient, then the number of P4s in P3 is 1, n, n(n+1)/2, or n². If P3 is an a, f, q, g, h, r, or da coefficient, there is one P4. If P3 is an α, γ, or β coefficient, there are “n” P4s.

Level 4 (value level): A single item including a symbolic text expression for computing PDE coefficient values. The expression may be evaluated where the variables xi, sd, ui, uixj, and h correspond, respectively, to representing the ith coordinate, subdomain label, ith solution component, jth derivative of the ith solution, and the local element size. ui and xj may refer to the variable names defined by fem.dim 256 and fem.sdim(independent variable names or space coordinate names), respectively. It should be noted that fem.sdim may be an additional field included in the portion 270 of data structure 250 in an embodiment.

What will now be described is one embodiment of a method for converting application mode physical properties on subdomains and boundaries into a PDE form, either general or coefficient. In other words, once data is input and stored in the structure 250, this data may be expanded or transformed into another form used in subsequent processing steps. In other words, the following may be used in connection with converting GUI data into PDE format for each application mode.

It should be noted that in the following example, the GUI or input data is stored in a temporary or tmp structure for each application mode. The combined system of PDEs may be formed using as input each of the tmp structure for each application mode. An embodiment may store a representation of the combined PDE system in the fem structure as described in more detail elsewhere herein.

The application mode properties in the fields equ and bnd in the appl {i} structure are rewritten as symbolic expressions by using an application mode dependent set of transformation rules, e.g., for heat transfer.

-   -   tmp{i}.equ.c{j}=appl{i}.equ,k{j};     -   tmp{i}.equ.a{j}=appl{i}.equ.htrans{j};     -   tmp{i}.equ.f{j}=appl{i}.equ.Q+appl{i}.equ.Text{j}+appl{i}.equ.Camb{j}*(appl{i}.equ.Tambtrans{j}̂4−appl{i}.dim̂4)     -   tmp{i}.equ.da{j}=appl{i}.equ.rho*appl{i}.equ.C{j}     -   by looping over the subdomain index j. The field appl{i}.dim is         the physical quantity, the temperature. Similarly the boundary         subdomain properties are rewritten by the rules:     -   tmp{i}.bnd.q{j}=appl{i}.bnd.h{j};     -   tmp{i}.bnd.g{j}=appl{i}.bnd.q{j}+appl{i}.bnd.h{j}*appl{i}.bnd.Tinf{j}+appl{i}.bnd.Const{j}*(appl{i}.bnd.Tamb{j}̂4−appl{i}.dim.̂4);     -   when the type is QG and as     -   tmp{i}.bnd.h{j}=1;     -   tmp{i}.bnd.r{j}=appl{i}.bnd.T{j};     -   when type is T.         The remaining type cases, QG0 and T0, are simple cases of the         above cases, where all left hand side terms are zero, except the         bnd {i}.h term.

It should be noted that the foregoing rules to produce symbolic expression may vary with application mode. For example, the foregoing rules may be used in connection with forming coefficients for heat transfer application mode. As known to those of ordinary skill in the art, the techniques may be applied to forming coefficients for other application modes. It should be noted that functionality associated with the above description is included in one embodiment as a function “appl2fem” as described in the FEMLAB V1.1 Reference Manual from Comsol AB, 1999.

The foregoing may be performed for each of the application modes, i, to expand or transform data into PDE form data included in the application mode structure tmp{i}. This structure tmp{i} includes a representation of the physical properties as instances of the PDE formulae of FIG. 8 or FIG. 9.

The fields usage and border for the tmp data structure may be copied from the corresponding fields in the data structure 250. The field dim 256 may be updated with another variable name, and introduce a relation between the physical quantity and the dependent variables, and introducing this relation when the equ and bnd fields are transformed into the tmp structure.

The submode setting described elsewhere herein in more detail, for example, in connection with FIG. 3, may be used in determining the number of variables. The submode setting may be used to distinguish between a stationary and time-dependent problem. In certain application modes, such as structural mechanics, the number of dependent variables in the application mode may vary in accordance with a submode setting or selection. For example, PDE formulation as described in connection with FIG. 8 does not provide for a second order time derivative. Thus, for example, in application modes related to structural mechanics, where the displacements are the dependent variables, it may be desirous to add the velocities of the displacements as dependent variables in addition to the displacements. Thus the application mode describing the system may include twice the number of variables for the time-dependent subdomain than for the stationary.

What has just been described are processing steps that may be included in an embodiment in connection with expanding or converting input data, as using the GUIs, into a PDE form, such as general or coefficient.

An embodiment may continue by merging the formulae associated with a plurality of application modes and PDEs into a single system of combined PDEs. Appending the subsystems in the order they are specified in each of the fem.appl 254 creates the composite system. In one embodiment, the affected fields in the data structure 250 structure may include dim 256, form (additional field in area 270 indicating problem form as general or coefficient in this example), equ 258, bnd 260, border 262, and usage 264.

The dim field 256 of the composite system may be obtained by concatenating the dim field lists from each of the application modes appl {i}254. The default form of the composite system is the most general form of the subsystems, where “general” is the most general form, and “coefficient” is the least general form.

The conversion of a PDE in coefficient form to general form is described elsewhere herein. The output form may be “forced” to general form by forcing the conversion also if none of the appl{i} application modes are specified in general form. A value may be stored in an additional field that may be included in an embodiment of the data structure 250, such as an additional field in the area 270, indicating the type of problem form, for example, as one of general or coefficient in this embodiment.

The equ 258 and bnd 260 fields in the data structure 250 may be determined using corresponding fields appl{i} in the application modes, after each application structure has been converted to the representation of the PDEs, and the desired output form, according to FIG. 11. The coefficients in the second row may be deemed “weakly” coupled in the sense that the corresponding coefficients in the composite system are block diagonal. This may limit the coupling between the subsystems. By using general form, however, there are no limitations on the composite system. In this embodiment, the border field 262 in the data structure 250 may indicate a list of on/off, one for each solution component. The usage field 264 may be determined using the usage matrices, such as 254 e of each subsystems, by concatenating usage lists as rows in a matrix.

Thus, one technique for combining PDEs may be represented by the following pseudocode-like description:

Gpos=0; for i=1 to Nappl j=Ndim (i); for k=1 to Nsub fem.equ.da{k}(gpos+(1:j),gpos+(1:j))=tmp{i}.equ.da{k}; fem.equ.c{k}(gpos+(1:j),gpos+(1:j))=tmp{i}.equ.c{k}; fem.equ.al{k}(gpos+(1:j),gpos+(1:j))=tmp{i}.equ.al{k}; fem:equ:ga{k}(gpos+(1:j))=tmp{i}.e.qu.ga{k}; fem.equ.be{k}(gpos+(1:j),gpos+(1:j))=tmp{i}.equ.be{k}; fem.equ.a{k}(gpos+(1:j),gpos+(1:j))=tmp{i}.equ.a{k}; fem.equ.f{k}(gpos+(1:j))=tmp{i}.equ.f{k}; end for k=1 to Nbnd fem.bnd.q{k}(gpos+(1:j),gpos+(1:j))=tmp{i}.bnd.q{k}; fem.bnd.g{k}(gpos+(1:j))=tmp{i}.bnd.g{k}; fem.bnd.h{k}(gpos+(1:j),gpos+(1:j))=tmp{i}.bnd.h{k}; fem.bnd.r{k}(gpos+(1:j))=tmp{i}.bnd.r{k}; end fem.border(gpos+(1:j))=tmp.border(1:j); fem.usage(gpos+(1:j),:)=tmp.usage(gpos+(1:j)); gpos=gpos+j; end

In the above description, the “Nsub” denotes the number of subdomains in the geometry, “Nappl” denotes the number of application modes, and “Nbnd” denotes the number of boundaries. “Ndim(i)” is the number of dependent variables of the application mode.

The result of performing the foregoing is the data representation of the system of PDEs corresponding to the full multiphysics system of the combined PDEs for the selected application modes. In an embodiment, the above procedure is documented as function “multiphysics” in the FEMLAB V1.1 Reference Manual.

It should be noted that if the systems represented in the structure tmp{i} are converted to general form, the foregoing pseudocode description may be applied to the coefficients, for example, as represented by ga (corresponding to “gamma”), f, g, r.

An embodiment may include storing the data for the PDEs and boundary conditions for each application mode in a more compact format using, for example, the ind field in appl{i}.equ and appl{i}.bnd. In one embodiment, as also described elsewhere herein, the ind fields may be implemented each as a vector with length equal to the number of subdomains or boundaries. For each subdomain, the corresponding entry designates a domain group or 0 for no group. Similarly the field bnd.ind has the corresponding meaning for boundaries. When the ind field is not given, each subdomain or boundary forms a separate group. It should be noted that when using this compact format representation feature and the appl{i}.equ.ind or appl{i}.bnd.ind fields are different for the selected application modes, the ind fields may also be merged or combined into the ind fields in fem.equ.ind (subfield of 258) and fem.bnd.ind (subfield of 260). These fields may have a minimal common set of subdomain or boundary groups. This may be determined, for example, by jointly sorting the groups in the application modes and removing duplicates.

In one embodiment, the solution procedure uses the Finite Element Method (FEM) to solve the system of PDEs in coefficient and general form, for example, as represented in FIGS. 8 and 9. This is described, for example, in “The Mathematical Theory of Finite Element Methods”, S. C. Brenner, L. R. Scott, Springer-Verlag, ISBN 3-540-94193-2. This is a well-known procedure, but has been adapted to specifically fit a particular context of one embodiment. In this embodiment, the first equation in FIG. 8, element 142, and the first equation in FIG. 9, element 152, may be multiplied with an arbitrary test function v, and integrated over the domain Ω, such as integrated by parts, for example, using Green's formula. The boundary integral may be replaced using the Neumann boundary condition. Furthermore, the Dirichlet boundary condition may be multiplied by an arbitrary test μ function and integrated on the boundary, and obtain the variational formulation of the full problem: Find μ_(k) and λ_(m) such that for all v, m, l=1, . . . , N, and m=1, . . . , M the equations in FIG. 12 and FIG. 13 hold, for coefficient and general form, respectively.

As described in connection with one embodiment, the PDE system to be solved may be passed to a solver algorithm for PDEs that uses the finite element method. In addition to the data structure 250 that may include the representation of the PDEs, two sets of constraint matrices may be used and are referred to and described in more detail elsewhere herein in connection with particular features that may be included in an embodiment.

The finite-dimensional function space is the set of piecewise linear functions on a triangulation τ of the domain Ω. u and Λ may be approximated, for example, using the formulae 304 of FIG. 14, where φ_(l) is linear on each element, continuous, and 0 on all node points in the triangulation except the node point I. ψ_(K,L) is a delta function at a vertex L on a boundary element K.

By using the test functions φ_(J) and ψ_(K,L) on the weak form of the PDE in coefficient form, it may be determined that the formulae 306 of FIG. 15 applies for all J and l, and that the formula 308 of FIG. 16 apply for all K, L, and m. The finite element discretization represented by 310 of FIG. 18 may be determined. It should be noted that the integrals as included in the formulae 310 of FIG. 18 may be computed using a Gauss quadrature within each element. The formula corresponding to those of 306 of FIGS. 15 and 308 of FIG. 16 for general form may be represented as in formulae 312 of FIG. 17.

With reference to the data structure 250 described elsewhere herein, when the integrals in 310 of FIG. 18 are computed, the initial value in fem.init 266 may be used as values for the solution when it occurs in the expressions in the PDE coefficients and boundary conditions.

By numerically computing the matrices according to the foregoing formulae, the systems of equations represented in FIG. 19 and FIG. 20 may be determined. In particular, referring to FIG. 19, shown are formulae 320 in coefficient form, and referring to FIG. 20, shown are formulae 322 in general form, in which C, AL, BE, A, and Q are N_(P)N-by-N_(P)N matrices, and F, GA, and G are N_(P)N vectors. H is a N_(e)nM-by-N_(P)N matrix and R is a N_(e)nM vector. The DA matrix is used in time-dependent and eigenvalue problems. When these matrices are produced, the first index in the index list in FIG. 18 is expanded first.

Linear solvers, nonlinear solvers, time-dependent solvers and eigenvalue solvers may be used in solving systems of PDEs of FIG. 19 in coefficient form, and PDEs of FIG. 20 in general form. Such solvers, or solving techniques, are generally known in the numeric literature, for example, such as in “Numerical Methods”, G. Dahlquist, {dot over (A)}. Björk, Prentice Hall, 1974, ISBN 0-13-627315. In one embodiment, a technique may be used to generate the Jacobian for nonlinear solvers and for solvers of time-dependent problems. This technique may be used in systems in general form, or PDE systems that have been converted from coefficient form to general form, for example as described in connection with the formulae 240 of FIG. 11.

It should be noted that use of PDEs in general form may be used to more efficiently provide PDE solutions in solving for non-linear systems of equations. One technique, as described elsewhere herein in more detail, may utilize the general form to derive a Jacobian. This may be more efficient than using the coefficient form for solving for non-linear systems. Using this general form to derive the Jacobian, the Newton method may then be used. FIG. 10 shows an iteration of using the Newton method.

For the combined system or multiphysics, the solution may be stored in the field fem.sol 268 of the data structure 250. In one embodiment, the solution field 268 may represent the solution to a PDE system as a vector having the same number of elements as the corresponding U. Similarly fem.init 266 may include the initial value for the nonlinear and time-dependent solvers. For time-dependent solutions, there may be several columns in fem.sol 268, one for each point in time.

In one embodiment, nonlinear equations in general form may be solved by Newton iterations.

Referring now to FIG. 11, shown is an example of the formulae that may be used in an embodiment in converting from coefficient to general form of the PDEs. The conversion from coefficient to general form may be performed on the app{i} structure for each application mode separately in accordance with the form desired, for example, as may vary in accordance with equation or system type. For example, if a system being solved is in coefficient form and it is a non-linear system, it may be desired to convert from the coefficient form to general form using the formulae 240 of FIG. 11 in conjunction with the other formulae 140 for coefficient form to produce a system of PDEs of the general form, such as those represented by the formulae 150 of FIG. 9. This conversion may also be performed in accordance with a user selected or specified mode, for example, as may be included in an embodiment. Other embodiments may perform this conversion from coefficient to general form in connection with other function that may be included and vary with implementation.

The formulae 240 of FIG. 11 may be used to derive Γ, F, G, and R from d_(a), c, α, γ_(l), β, a, f, q, g, h, and r as included in the formulae 140 of FIG. 8. This may be performed, for example, as by symbolic manipulation of the mathematical expressions.

The discretization by the finite element method, given a nonlinear system of equations in as in the general form of FIG. 20, may be viewed as the problem p(U)=0, where U is the vector of unknown coefficients of the finite element solution to the PDE problem. In this instance, DA=0 since this problem is stationary. The LaGrange multipliers, Λ, may be considered auxiliary values Λ=Λ(U) which may be assumed to be eliminated. For the solution of the discretized system, an affine invariant form of the dampened Newton method may be applied: Given an initial guess, U⁽⁰⁾; a sequence of iterates U^((k)) is computed by the iteration formula 326 in FIG. 21, where J(U)=∂ρ(U)/∂U, and λ_(k)ε(0; 1] denotes a damping factor.

Subsequently solving for ΔU^((k)) above may utilize the solution of a linear system of equations. If J(U) is chosen as the exact Jacobian, the iteration formula above may be interpreted as the finite element discretization of a linearized equations in coefficient form by applying the settings in 324 of FIG. 10. The coefficients in the coefficient form PDE may be formed as symbolic derivatives of the coefficients in the general form PDE with respect to the solution, and its gradient.

It should be noted that the “Active in this subdomain feature” for selective inclusion or variation of a variable in a system, may be implemented in one embodiment by adding a constraint to the H and R matrices to not-a-number in IEEE arithmetic. One row containing the constraint may be added to H and R for each node point in the deactivated subdomains and dependent variables.

It should also be noted that when the system of PDEs is assembled, for example, according to FIG. 18, the variables not to solved for may be used in the expressions for PDE coefficients and boundary conditions. In one embodiment, the “solve for variable feature” may be implemented by adding a constraint to the H and R matrices that constrains the solution in the node points the value of the previous solution in the same point, one row containing the constraint is added to H and R for each node point and dependent variable.

The foregoing description may be used in forming a multiphysics model and solving for selected variables. Steps of one embodiment may be summarized in the form of a flowchart and accompanying description.

Referring now to FIG. 22 and FIG. 23, shown is an example of an embodiment of a flowchart of steps of one method for automatically specifying one or more systems of PDEs, representing them in a single combined form, and solving a system of PDEs. At step 210, a first application mode is selected. It should be noted that each application mode corresponds to a particular system being modeled. The selection of one or more application modes may be performed, for example, in one embodiment using the GUI 30 of the previously described FIG. 3. At step 212, a determination is made as to whether the processing steps formed by the loop at the top of step 212 are complete for all application modes. If a determination is made at step 212 that processing of all the applications modes selected at step 210, control proceeds to flow point A. Otherwise, control proceeds to step 214, where the physical properties associated as active with the current application mode are determined. The physical properties associated with an application mode may be selected, for example, in connection with GUI 60 of FIG. 4. Control proceeds to step 216, where the boundary condition for the current application mode is determined. The boundary conditions may be determined, for example, using the GUI 70 of the previously described FIG. 5.

Control proceeds to step 218, where data structures are created and initialized using the physical properties and boundary conditions specified for the current application mode in connection with the processing, for example, of steps 214 and 216. At step 220, the coefficient PDEs may be formed using physical property and boundary data obtained in connection with steps 214 and 216, and accordingly stored in the data structure created and initialized at step 218. Recall, as previously described, that the PDE in coefficient view, or form, may be represented as described in connection with the formulae 140 of FIG. 8. Additionally, recall that a temporary data structure may also be used when forming the coefficients for each application mode. At step 222, the general form of the PDE may also be formed. Accordingly, the data structure initially created at step 218 may be updated to include the information about the general form for the PDE system. It should be noted that the general PDE formed at step 222 may be as represented by the formulae 150 previously described in connection with FIG. 9. A temporary data structure may also be used in storing data for the coefficients formed in connection with processing of step 222, similar to that as may be used in connection with step 220.

An embodiment may provide an option to allow for data entry, display and modification in coefficient form, general form, or both of these forms. If more than one is included in an embodiment, there may be a default, or a user selection option. Thus, processing associated with steps 220 and 222 may be optionally performed in accordance with what may be included in an embodiment, and may additionally be in accordance with a user selection. One embodiment provides for data entry, modification, and PDE solving associated with an application mode in either coefficient view or general form. Coefficient view may be selected for data entry and modification with the additional user input selection of producing general form, and solving PDEs using either form. If general form is selected for data entry without coefficient view, PDE solving may be performed, by default, using a system of equation in general form. As known to those of ordinary skill in the art, in accordance with the PDE system being solved, solving using the general form may be more efficient and desired over use of coefficient form. For example, in solving PDE systems for non-linear systems, use of the general form may be more efficient.

At Step 224, an embodiment may include, optionally, functionality to modify the boundary conditions and/or PDEs of the current application mode. It should be noted that if an embodiment includes the function of modifying a PDE for each application mode, the previously described locking mechanism may operate differently since PDEs may change per application mode.

At step 226, a next application mode may be selected. Control proceeds to step 212 where a determination is again made as to whether processing all the application modes is complete.

When all the application modes are selected and done being processed in connection with the processing steps formed by the loop beginning with a decision at step 212, control proceeds to flow point A, step 230, where PDEs for all the previously entered application modes are combined, forming a combined PDE system. In other words, the result is a single PDE system representing the combination of all the previously described systems in connection with all the previously specified application modes. It should be noted that in one embodiment described in more detail elsewhere herein, data associated with the PDE of each application mode may be stored in a temporary structure for each application mode. At step 230, in this instance, the temporary data structures may be used as input for producing the combined PDE system or multiphysics system of PDEs. At step 231, an embodiment may optionally provide for modifying the combined PDE system, or other systems. Control proceeds to step 232, where the PDEs, or variables associated with PDEs, may be solved. An embodiment may provide variations as to what variables or PDEs may be solved for in the processing of step 232. One embodiment may allow the user to select solving for one of the PDEs associated with individual application modes, the combined PDE system, or variables from different PDEs. Control proceeds to step 234 where the processing of the flowchart 200 stops.

What has just been described is the general processing of the overall system for automatically forming one or more sets of PDEs associated with one or more application modes or systems. These systems may be combined into a single, combined PDEs system. A programming module, such as the finite element solver that may be included in the Modeling and Simulation Module 222, may solve a system of PDEs. The finite element solver, for example, may solve a single system of PDE corresponding to a single application mode, may solve for the combined PDE system, for example, as computed or determined in connection with the processing step 230. An embodiment may also solve for one or more variables associated with one or more application mode using any one of a variety of known solving techniques.

What will now be described in more detail is how user defined application modes and user defined applications may be used in the foregoing system and with the techniques described herein. Generally, a user defined application mode in one embodiment may be an equivalent to a predefined application mode, such as heat transfer, described elsewhere herein. An “application mode” is distinguishable from an “application”. In this embodiment, an application may be associated with a user defined subclass from a class, for example, that may be associated with an application mode. An application may be defined by a user, for example, when it may be useful to create a specialized or narrower definition of an existing class corresponding to an application mode. In this way, routines and code common in more than an application may be shared since, fore example, in this embodiment, functionality of one or more applications (subclasses) may be inherited from an application mode.

Alternatively, a user-defined application mode rather than a user defined application may be more appropriate, for example, when such functionality is not common or bears little or no relationship in functionality to an existing application mode.

In one embodiment, an application mode may be predefined, such as Diffusion or Heat Transfer included in one embodiment of the software 19, or user-defined. User-defined application modes may be created using an Application Program Interface (API), such as those described in the FEMLAB V1.1 Application Program Interface manual. In contrast to the user defined application mode is the user-defined application. A difference between the user-defined application mode and user-defined application is that a user-defined application may be much more specialized, for example, regarding the geometry, modeling, meshing and the GUI appearance. Use of the API allows users to add new functionality to FEMLAB or remove functionality in order to tailor software of an existing application mode to better fit a particular use as may be associated with a particular user-defined application.

In one embodiment, a user may create and define a user-defined application mode and application. These may be created using classes and subclasses in connection with an object oriented approach in which use of objects and classes allows for the addition of new data types and operations, for example, as may be implemented using MATLAB. The operations and functions that operate on class objects are known as methods collected together in a class directory. The class directory includes a constructor for that class. Generally, a predefined application mode, such as one for heat transfer, may be created as a class. A user defined application may be defined as a subclass of one of these classes. In this manner, the functionality of an existing application mode may be inherited by a new user defined application with additionally having some or all of its functionality overloaded by a subclass allowing for a user to create an application with desired behavior. An application mode may also be defined a the same level as the predefined application modes, such as heat transfer. These user defined application modes may have the same status and use as the predefined application modes. In particular, both predefined and user defined application modes may be used as one of the application modes, for example, when forming a combined multiphysics system as described in more detail elsewhere herein.

An application mode may be created as a class. These classes may be represented in a hierarchical structure. There are a set of base classes at the top of a hierarchy containing the main functionality. The application modes may inherit from base classes, sometimes through convenient intermediate classes that may include methods defining functionality common to several application modes. An example of the class hierarchy may be found in FIG. 24, element 500, as described in more detail elsewhere herein. An application mode may be created by defining parameters on the boundary and the inner domain that will define the equations to be solved, and how to specify these parameters in the GUI. For more streamlined design of the application modes, the available solvers and the initial conditions, post processing expressions, and name of dependent and independent variables may also be modified.

An application mode has a constructor, for example, such as in connection with FIG. 28 described in more detail elsewhere herein. The information for an application mode may be stored in the application mode object and in the fem.appl-structure also described elsewhere herein. Table 510 of FIG. 27 includes properties that may be included in one embodiment of an application mode object. These properties are either inherited from the parent objects, or may also be set explicitly. Table 514 of FIG. 29 includes a listing of the methods that may exist either directly in the application mode class, or in any of the parent classes. The column to the right in this table 514 describes what the methods do.

Additionally, a set of methods may be used by the GUI to set up solvers and dialog boxes as well as submodes for the application modes. In one embodiment, these methods are:

bndinfo sets up boundary conditions dialog box equinfo sets up PDE coefficients dialog box pdeinfo contains info about available solvers, solution forms, and submodes sub_conv gives the relation between old and new variables when changing submode

Other important methods are the set and get methods that allows for setting and getting of the application mode object properties.

In one embodiment, to define a user-defined application mode, a minimum set of definitions and routines or methods are defined. These include the constructor, appspec, bnd_compute, and equ_compute. appspec is a routine for defining the parameters used in the interior and on the boundaries. Routines equ_compute and bnd_compute define how to set up the equations based on this information from appspec.

In order to use the application mode from the GUI the equinfo and bndinfo methods may be implemented in the application mode class. These methods define how to set up the dialog boxes in the GUI for specifying the parameters.

In contrast to a user-defined application mode is a user-defined application. In the user-defined application, for example, overloading may be performed of some or all of the above methods, in addition to the methods for setting up the GUI, for example, such as fldrawmode, flboundmode, flpdemode, flmeshmode, flsolvemode, flplotmode in connection with set up some of the menus and toolbars for draw, boundary, PDE, mesh, solve and plotmode, respectively.

Referring now to FIG. 24, shown is an example of a class structure that may be included in an embodiment in which a user may define application modes. At the base of the class structure is the class flbase to facilitate overloading of generally provided functionality that may be included in an embodiment. The application mode object structure may divide the application mode objects in accordance with two particular criteria: geometry dimension and application modes. For geometry dimension, there are two geometry dimension dependent base classes fld1 and fld2 in which methods may implement dimension dependent functionality, such as draw mode menus, toolbars, mesh drawings, and the like. For application modes, there are three application module base classes of: flpde, which is the parent of all application modes, flsme and flcem which are other classes that may be defined in accordance with other modules and associated functionalities. In flpde, all functionality may reside that is common to all application modes and that is also not dependent on geometry dimension. All application modes may be implemented as subclasses to this class. Additional application-dependent classes may be added to support new applications. They may, for example, be implemented as subclasses of flpde or another application mode. In these class directories, methods that implement application dependent functionality, such as specific dialog box information, and the like may reside. Referring to the structure of the hierarchy illustrated in 500, the application dependent classes take precedence over the geometry dimension classes which also take precedence over the application module class so that, for example, a mesh drawing method in the flpde class may be overridden by the generic 2-D mesh drawing method. Note that the structure 500 may be only a portion of the entire class structure included in an embodiment.

Together with methods, the application objects may define specific properties and behaviors that define an application in the GUI. Referring to FIG. 25, shown are sample 1-D (one-dimensional) application modes 502 and 503. In combination, these two tables may define all predefined application modes included in one embodiment. All 1-D application objects inherit from the application module base class flpde and the geometry class fl1d.

Referring now to FIG. 26, shown are 2-D (two dimensional) application modes that may be defined in an embodiment. The application modes defined in 506 and 508 may include all application modes for 2-D application mode objects. All 2-D application mode objects may inherit from the application module base class flpde and the geometry base class fl2d. All of these classes are subclasses of fl2d and an application mode class. The application mode classes, in turn, are subclasses of flpdec or flpdeg that represent the coefficient and general PDE form, respectively. Note that the PDE mode classes flpdec1, flpdeg1d, flpdec2d and flpdeg2g all accept the number of dependent variables as an input argument thus enabling the creation of PDE modes with an arbitrary number of dependent variables. Calling the constructor function without a dimension argument results in a scalar application mode object.

Referring now to FIG. 27, shown is an example of properties of one embodiment of an application object. Table 510 describes various properties of application objects. Parent is string containing the name of the object class parent. The dim, name and parent properties are initialized explicitly using the application class constructor. Other fields may be inherited by the parent class but may also be initialized using the constructor.

In one embodiment, the application being defined by a user may be a subclass to one of the application mode classes. In one example, suppose a user wants to define a new application, myapp, based on the 2-D heat transfer mode flpdeht2d. A subdirectory may be created in a MATLAB path called @myapp. An example of a constructor may look as in the code snippet 512 of FIG. 28. In this example, the settings for submode, form, tdiff and sdim are from the parent class flpdeht2d. The dim property is explicitly set to be default as may be defined by the method default_dim.

In this embodiment that may use MATLAB, the behavior of MATLAB operators and functions for object arguments may be changed by overloading the relevant functions. This may be accomplished by defining a replacement method with the appropriate name residing in the new class directory at the application level. A user may minimize the number of overloaded methods in an application class being defined by a user by choosing the most appropriate application mode as its parent class. By using the overloading functionality, parts of an existing application may be modified to create application dependent functionality. For example, portions of a GUI, including menus, toolbars, and the like, may be modified to better fit an application as well as methods for overloading the equation definitions.

One embodiment may include a set of methods to provide a portion of the functionality. Referring now to FIG. 29, shown is an example of an embodiment of a portion of functions that may be included in one embodiment. The functions 514 may determine the variables and equations defining a problem. As described in more detail elsewhere herein, it should be noted that the appl field of the fem structure includes application dependent data. Appl is a cell array that contains more than one application mode for multiphysics problems. The foregoing methods may work in connection with a GUI and from the command line. The conversion from the application mode structure in the appl field(s) may be performed by invoking a function called the multiphysics function, which in turn uses another function to compute the equ, bnd, init, dim, usage, border, var, and form fields.

API functions may be included in an embodiment, for example, to allow for adding menus and toolbars to the existing GUI. Additionally, overloading methods may be used, for example, to disable certain functionality associated with a method or provide for an alternative.

Referring now to FIG. 30, shown is an example of a GUI that may be used in connection with adding an application to the existing GUI. Using the New tab in the GUI 520, a user may browse through the applications. The procedure of adding a new user-defined application may be performed using an API function, for example, fladdappl. Using such an API, an application may be added to the application tree and, optionally, associated text and FIG. The description and FIG. may be displayed when the user defined application is selected. For example, the GUI 520 has a user defined application of “IN-PLANE WAVE GUIDE” selected in 522. Accordingly, an associated image is displayed in 524 and text in 526.

What will now be described is another example of a user-defined application for modeling transmission signals with frequencies in the microwave range, for example, as may be used in the telecom industry. The waves are transmitted through a waveguide with a rectangular cross section. If the wave is bent, the elbow may cause scattering effects preventing the wave from being transmitted through the waveguide. In the following model, a TE wave is modeled in which there is no electric field in the direction of propagation. The dimension of the waveguide and frequency are chosen so that the only mode that can propagate is the TE₁₀ mode, that is where the electric field has only one non-zero component that is sinusoidal and vanishes at the walls of the waveguide.

A waveguide may be designed to transmit only frequencies in a narrow band. This band-pass effect may be achieved using a resonance cavity formed by putting conducting posts protruding into the waveguide. The posts may be, for example, metal screws or tuning screws. Equations used to calculate effects may be derived from the wave equation. Time may be eliminated assuming a harmonic planar wave resulting in Helmholtz equation for non-zero electric field component as represented by equation 530 in FIG. 31 in which k is the wave number in the propagating direction. The relation between the wave number k and the frequency f and wavelength λ is represented by equation 532 in which c denotes the speed of light.

In this instance, there are three kinds of boundary conditions in the model. At the entrance boundary in which there is a vertical line at x=0, there is an absorbing condition with an incoming sinusoidal wave as in equation 534. The right hand side of 534 is the driving force of the incoming wave. d is the width of the waveguide and yo is the y coordinate of the lower left corner of the waveguide. The wave number depends on the wave number in the direction of propagation ky as in 536. 536 may be derived from solving analytically for a straight waveguide the wave number in the transversal direction may be defined by twice the width of the waveguide. This results in the final expression for the wave number in the propagating direction as a function of the incoming wavelength and width of the waveguide according to 538. At the exit boundary there is an absorbing condition represented as 540 and the walls are assumed to be perfect conductors so that the tangential component of E vanished as in 542. The velocity of light may be calculated from the material parameters and the wavelength is calculated from the frequency and velocity. The cut-off frequency may be calculated from the analytical solution of a straight waveguide as in 544. No waves below this frequency are transmitted through the waveguide.

Using the foregoing waveguide and techniques disclosed herein, the foregoing complexity may be hidden using a GUI. A feature called frequency analysis may be implemented in connection with the waveguide application. What will now be described is an overview of how this may be implemented in one embodiment.

The draw mode for this feature may be implemented using overloading to implement an alternative draw menu and corresponding toolbar buttons. Toolbar icons may be stored in the application class directory as bitmaps. In this example, the draw menu is an alternate menu that includes 5 items: draw mode, straight waveguide, elbow waveguide, geometry parameters and the standard draw menu item Properties. The draw toolbar contains the toolbar buttons straight waveguide, elbow waveguide and geometry parameters. In connection with each of the waveguides, a corresponding FIG. or image may appear in the GUI. Parameters may be varied in accordance with each of the waveguides by overloading existing methods, for example, by overloading an existing method objdlg in which the geometry is parameterized and the parameters may be stored in a user defined portion of the fern structure on creation. It should be noted that this is a portion of memory allocated for use by the user and not used in this example by the existing methods. Additionally, other functionality may be disabled using overloading, such as to disable importing geometries and cut and paste functionality.

Boundary conditions are “hardwired” according to the equations depending on parameters, for example, as may be defined in the PDE specification GUI. The Boundary menu and related mode buttons may be completely removed using overloading of existing methods. Existing methods are used to define the boundary conditions. Some of the standard PDE mode menu items are removed by overloading the existing method(s). The mesh mode remains the same. Similarly, other modes that are defined and there GUIs, toolbars and the like, may be used and techniques, such as overloading, may be used to implement these as may be desired in accordance with this example and others.

In connection with the waveguide, due to the conversion of time-dependent PDE to a harmonic wave equation, the existing application mode AC Power Electromagnetics mode may be used. The new waveguide application being defined may be implemented, for example, as a subclass to its class, @flpdeac. the waveguide class, named @flwaveguide, may be created on the same directory level as the parent class @flpdeac. An example class constructor is included in 550 of FIG. 32.

Parameters of the waveguide may be specified as in 552 of FIGS. 33 and 554 of FIG. 34. The entrybnd and exitbnd fields may be used by a bnd_compute method to set the appropriate boundary conditions. The startpt field may be used to define the incoming sine wave on the entry boundary. The freqs field includes the frequency vector that may be used by the frequency analysis feature.

The geomparam structure is a 2 element structure array including geometry parameters for straight and elbow waveguides that may include fields as in 556 of FIG. 35. The geometry boundaries may be formed by a set of existing objects using the parameters entrylength, exitlength, width and radius. These existing objects may be combined into a single new geometry object using, for example, an API that forms a single object that is a cell array containing the existing objects.

If the resonance cavity is operative, such as by checking a resonance cavity checkbox on one of the GUIs, the protruding posts are subtracted from the geometry. In this instance, the posts may be creates as a set of solid rectangular objects using the specified cavity parameters. The resulting mapping matrices representing this subtraction result may relate the curve and point indices in the input geometries, respectively, to their new indices in the new geometry object. Knowing the order in which the basic object were created to make the new geometry, the index corresponding to each of these basic objects in the final geometry may be calculated and stored in the user structure.

Of the existing methods previously described in connection with 514 of FIG. 29, 6 may be overloaded. These may include, for example: default_equ, equ_compute, default_bnd, bnd_compute, default_var, and posttable. Equ_compute returns the PDE coefficients computed from parameters defined in the appl.equ structure. The ind field includes 1 since there is only one subdomain. Default_bnd method defined default boundary conditions. Bnd_compute computes boundary conditions from the material parameters and the frequency defined in appl.equ. The entrybnd, exitbnd, and startpt fields in the fem.user structure are used to place the correct boundary conditions on the correct boundaries. Default_var returns an empty cell array disabling default scalar variables. It should be noted that this method may have been used to define the incoming frequency as a scalar subdomain-independent variable instead of as part of the appl.equ structure. In this instance, the frequency may be specified in connection with a different dialog box, such as Application Scalar Variables rather than in connection with the PDE specification dialog box. In posttable, the post processing data is defined. The output variables, descriptions an evaluation expressions may be defined.

Following is an overview of the overloaded GUI methods in the Waveguide application. It should be noted that the following GUI methods may be included in one embodiment. Other embodiments may include other methods or variations of these. Method appspec may be used to define the variable names in the bnd and equ structures of the fem.appl field. appspect for the waveguide may return a structure including fields defining the PDE variables to be scalars and the boundary variables to be boundary coefficients of problem dimension. This information may be used by the appl2fem routine, for example, as described in the FEMLAB V1.1 Reference Manual, FEMLAB V1.1 User's Guide, and FEMLAB V1.1 Model Library, by Computer Solutions (COMSOL) Europe AB. Parts of other functionality described herein may also be fund in the foregoing documentation. This information may also be used by the PDE specification dialog box. The method pdeinfo is used to define the default abbreviation for an application. Only the standard submode, coefficient form and stationary linear solver are available. The equinfo method returns equations, descriptions and parameter names to be displayed in connection with the PDE specification dialog box. The returned cell array of equations in this instance includes one equation due to the stationary linear solver being the only solver. The flboundmode method removes the standard Boundary menu from the GUI and the corresponding boundary mode toolbar is removed from the flviewtbg method. The importing of geometry objects may be disabled by the flimpmenu method returning an empty structure. Flmphmenu removes the multiphysics menu from the GUI by also returning an empty structure of menu handles. The flpdemode method returns a PDE menu structure including only 2 items, PDE mode and PDE specification. flsolvemode method returns a Solve menu structure includes the items solvemode, solveproblem, frequency analysis, and parameters. flmeshcolvtbg replaces the standard restart button with a frequency analysis button in which a corresponding icon is stored as a bitmap in a directory. Similarly, methods in connection with the geometry parameters, initial conditions and the like are modified and/or disabled in accordance with the desired GUIs and functionalities for the waveguide mode. Finally, the waveguide application may be added to the model navigator, such as in connection with the GUI displayed in FIG. 3, by invoking a function. In one embodiment, the following is an example invocation:

-   -   fladdappl(‘flwaveguide’, ‘In-plane Waveguide’)     -   in which a bitmap flwaveguide.bmp may reside in a class         directory. The bitmap may be displayed to the right of the Model         Navigator as previously illustrating in connection with GUI 520         of FIG. 30.

In another embodiment, a method is set forth that may be used in connection with specifying non-local couplings of multiphysics systems. This method may also be used in connection with local couplings, for example, as described previously. The method includes a scheme for defining a plurality of variables, as discussed in detail below. A non-local coupling, for example, may be used in coupling a value of a physical quantity from one portion of a domain to another portion of the same domain. In one embodiment, a non-local coupling may be used, for example, to specify couplings when the values of a physical quantity on a boundary of a domain are used in a partial differential equation along parallel lines extending into the domain. Additionally, a non-local coupling may be used, for example, in specifying a coupling when the value of the integral over a portion of a domain is used in the boundary condition of a partial differential equation. Local and non-local couplings as well as the variables that may be used with each type of coupling are described in more detail elsewhere herein.

Furthermore, the method can include an analysis of a multitude of geometries. The data structures used previously can be extended to multiple geometries by storing the previous data structure (fern data structure) in a list in the extended data structure (xfem). Both of these are described in more detail below. Generally, for a geometry number g, the field x in the extended data structure occurs as xfem.fem{g}.x, where xfem.fem{g} is the fern data structure repeated for each geometry in the extended data structure for multiple geometries. When using the multiple geometry data structure, the field xfem.sol contains the solution, and solutions are no longer stored in fem.sol for each geometry. A combined extended mesh for all the geometries is stored in the field xfem.xmesh. The coupling variables are stored in a list in the field xfem.elemcpl. The extended mesh structure xfem.xmesh is described in more detail elsewhere herein.

In one embodiment, there are three different forms of PDEs that may be used, namely, the coefficient form, the general form and the weak form. It should be noted that the coefficient form is most suitable for use with linear or almost linear problems whereas the general form may be used for the non-linear problems. The weak form of an equation is more general than the other two forms, and it is formulated as an equality of integrals. The weak form may be used, for example, in implementing point and line sources. A problem in coefficient form can be converted to general form, and a problem in general form can be converted to weak form. The coefficient form and the general form are described elsewhere herein in more detail.

Assume that there are a number of Euclidean spaces, each equipped with a collection of domains, i.e., volumes, surfaces, curves, or points. The domains may be approximately subdivided into mesh elements, constituting a mesh as described elsewhere herein using standard mesh generation techniques, for example, as described in the text by Frey, P. J. & George, P. L., entitled “Mesh Generation, application to finite elements”, HERMES Science Publishing, 2000. Commonly used mesh elements, as known to those of ordinary skill in the art, may include, for example, tetrahedrons, triangles, and line segments. On each mesh element, local (barycentric) coordinates may be defined, for example, as described in “Mesh Generation, application to finite elements” by Frey et al. Couplings including variables may be used to define relationships between multiple geometries as well as for a single geometry.

The starting point for the finite element method is a mesh, that is, a partition of the geometry into small units of a simple shape. In 1-D, the subdomains are partitioned into smaller mesh intervals or mesh elements. The endpoints of the mesh intervals are called mesh vertices.

In 2-D, the subdomains are partitioned into triangles or mesh elements. This is only an approximation, since a boundary can be curved. The sides of the triangles are called mesh edges and the corners mesh vertices. A mesh edge must not contain mesh vertices in its interior. Similarly, the boundaries defined in the geometry are partitioned (approximately) into mesh edges, boundary elements, which conform with the triangles if there is an adjacent subdomain. There may also be isolated points in the geometry that also become mesh vertices.

Similarly, for 3-D geometries, the subdomains are partitioned into tetrahedrons (mesh elements) having faces, edges and corners that may be respectively referred to as mesh faces, mesh edges, and mesh vertices. The boundaries in the geometry are partitioned into boundary elements (mesh faces). The edges in the geometry are partitioned into mesh edges. Isolated geometry vertices become mesh vertices.

It should be noted that mesh vertices are sometimes called node points. When considering a d-dimensional domain in the geometry, such as a subdomain, boundary, edge or vertex, then by its mesh elements, we mean the d-dimensional mesh elements included in the domain. An embodiment may include a function for creating and initializing a mesh structure described herein.

For each of the geometries described herein, there is a mesh. Once a mesh is defined using techniques also described elsewhere herein, approximations may be introduced for the dependent variables. For example, in considering a single variable u may be approximated with a function that can be described by a finite number of parameters also referred as the degrees of freedom or DOF. This approximation may be inserted into the weak equation to get a system of equations for the DOFs.

As an example, consider a mesh in one dimension consisting of two mesh intervals 0<x<1 and 1<x<2. Consider a variable u that is represented with linear finite elements. This means that on each mesh interval, the continuous function u is linear. Therefore, in order to characterize u, it suffices to specify the values of u at the node points x₁=0, x₂=1, and x₃=2. We denote these values U₁=u(0), U₂=u(1), U₃=u(2). These quantities U₁, U₂, and U₃ are called the degrees of freedom. The function u may be represented as:

u(x)=U ₁ f ₁(x)+U ₂ f ₂(x)+U ₃ f ₃(x)

-   -   where f₁(x) are certain piecewise linear functions, called the         basis functions. Namely, f_(i)(x) is the function which is         linear on each of the mesh intervals, and is equal to 1 at the         ith node point and 0 at the other node points. For example,

${f_{1}(x)} = \left\{ \begin{matrix} {1 - x} & {{{if}\mspace{14mu} 0} \leq x \leq 1} \\ 0 & {{{if}\mspace{14mu} 1} \leq x \leq 2} \end{matrix} \right.$

-   -   The set of functions u(x) constitutes a linear function space,         called the finite element space.

If better accuracy is desired, another finite element space corresponding to quadratic elements may also be considered. Functions u in this space are second order polynomials on each mesh interval. To characterize such a function u, node points can be introduced at the mid-point of each mesh interval. For example, x₄=0.5 and x₅=1.5. Accordingly, corresponding degrees of freedom may also be introduced for each of these points, U_(i)=u(x_(i)). Then on each mesh interval, the second degree polynomial u(x) is determined by the degrees of freedom at the end points and the mid-point. Accordingly,

u(x)=U ₁ f ₁(x)+U ₂ f ₂(x)+U ₃ f ₃(x)+U ₄ f ₄(x)+U ₅ f ₅(x)

-   -   where the basis functions f₁(x) now have a different meaning.         f₁(x) is the piecewise quadratic function that is 1 at the ith         node point and a zero at the other node points. For example,

${f_{1}(x)} = \left\{ \begin{matrix} {\left( {1 - x} \right)\left( {1 - {2x}} \right)} & {{{if}\mspace{14mu} 0} \leq x \leq 1} \\ 0 & {{{if}\mspace{14mu} 1} \leq x \leq 2} \end{matrix} \right.$

In general, a finite element space may be specified by giving a set of basis functions. The basis functions can be represented using local coordinates or element coordinates. For example, consider a mesh element of a dimension d in an n-dimensional geometry having space coordinates denoted x₁, . . . , x_(n) Also consider the standard d-dimensional simplex represented as:

ξ₁−0,ξ₂−0, . . . ξ_(d)−0,ξ₁,ξ_(d)U1

which resides in the local coordinate space parameterized by the local coordinates ξ₁ ξ_(d) If d=1, then the simplex is the unit interval. If d=2, then the simplex is a triangle with two 45 degree angles, and if d=3 it is a tetrahedron. Now our mesh element can be viewed as a linear transformation of the standard simplex. Namely, by letting the global space coordinates x_(i) be suitable linear functions of the local coordinates ξ_(k), the mesh element may be the image of the standard simplex. This means that in the local coordinate system, the corners of the mesh element have all ξ_(k),=0, except at for at most one k, for which ξ_(k)=1. When described in terms of the local coordinates, the basis functions may assume one of a few basic shapes, for example, as defined in the fern structure described elsewhere herein. With linear elements in 1-D, any basis function on any mesh element is one of the following:

φ=ξ₁φ=1−ξ₁φ=0

The first two above are the shape functions in this example. For quadratic elements in 1-D, the shape functions are

φ=(1−ξ₁)(1−2ξ₁)φ=4ξ₁(1−ξ₁)φ=ξ₁(2ξ₁−1)

The foregoing examples are special cases of the Lagrange element. To describe the Lagrange element, one needs to fix a positive integer k that is called the order of the Lagrange element. The functions u in the Lagrange finite element spaces are piecewise polynomials of the degree k such that on each mesh element, u is a polynomial of degree k. To describe such a function, it suffices to give its values in the Lagrange points of order k. These are the points whose local coordinates are integer multiples of 1/k. For each of these nodes p, there is a degree of freedom U_(i)=u(p₁) and a basis function f₁. The restriction of the basis function to a mesh element is a polynomial of degree at most k in the local coordinates such that f₁=1 at node i, and 0 at all other nodes. Thus, the basis functions are continuous, and

$u = {\sum\limits_{i}^{\;}{U_{i}f_{1}}}$

The Lagrange element of order 1 is called the linear element and the Lagrange element of order 2 is called the quadratic element.

What will now be described are different types of variables that may be included in an embodiment for use in defining local and non-local couplings. Other embodiments may include variables having different names and types including the concepts used herein. In one embodiment variables may be used which are functions on the domains. An embodiment may include basic variables, auxiliary variables, glued variables, mapped variables and integrated variables.

Basic variables may be defined and then other types of variables and new variables may be defined in terms of existing variables. For example, the auxiliary variables and the glued variables, which are discussed in detail elsewhere herein, may be used to implement local couplings between existing variables and new variables. A local coupling means that the value of a new variable in a point depends only on the values of the existing variables in the same point. A non-local coupling means that the value of the new variable at a point may depend on values of existing variables in distant points. Mapped variables and integrated variables, which are also discussed elsewhere herein, may be used to define non-local couplings between existing and new variables. In accordance with the method of this embodiment, it is possible to model physical quantities using local and non-local couplings.

In an embodiment, a basic variable V may be defined in terms of a number of basis functions Fi (i is an index). The notion of basis function is the usual one used in finite element analysis, see Zienkiewicz, O. C. & Taylor, R. L., The Finite Element Method, vol. 1, McGraw-Hill, 1994.

Each basis function is a function defined on some of the domains. Its restriction to each mesh element is a smooth function (often a polynomial in the local coordinates), and it is nonzero only on a few mesh elements. To each basis function there is associated a parameter Ui, which is called the degree of freedom (“DOF”). The variable V is defined as the sum of Ui*Fi over all indices “i”, where the “*” operator denotes a multiplication operation.

In the data structures of this embodiment, the basic variable names and their associated types of basis functions are stored in the fields xfem.fem{g}.shape, where g is the geometry number. This field is a list of shape function objects. Each shape function object defines a number of basic variables, and the basis functions that are used for these variables. In one embodiment using object oriented programming concepts written in, for example, C++, a number of methods may be applied on the shape function objects. For example, there is a method that may compute values of the basis functions which may be characterized as polynomial functions representing a shape function object. The domains of definitions for the basic variables are determined by the fields xfem.fem{g}.***.shape, where *** may be equ, bnd, edg, or pnt.

It should be noted that an embodiment may include a shorthand feature for defining which properties, shape function objects, and the like apply to a plurality of domains. The plurality of domains may be referred to as a domain group which is also referred to as the ind group or field described elsewhere herein. For example, a model may be defined in which a first set of material properties applies to 50 domains and a second set of material properties applies to another 50 domains. Rather than repeat the set of properties for each domain, a single set of defined properties may be defined and associated with a group of domains. An embodiment may include the concept of a domain group implemented in any one of a variety of different ways in which a single set of properties is commonly applied to a plurality of domains rather than use a 1-1 relationship to define and associate a single set of properties with a single domain.

Auxiliary variables of an embodiment may be defined by letting V1, V2, . . . , Vn be a number of variables, which are all defined on some domain. The auxiliary variables can be further defined by letting E(V1, V2, . . . , Vn) be a function of these variables (an expression). Then an auxiliary variable W can be defined in the following way: W=E(V1, V2, . . . , Vn).

An embodiment may define glued variables using a number of disjoint domains that are numbered 1, 2, . . . , n. The glued variables can be further defined by letting V1, V2, . . . , Vn be a number of variables, where Vk is defined on domain number k. Then a glued variable W can be defined on the union of the domains in the following way: W=Vk on domain k, for all k.

An embodiment may define the mapped variables by letting F be a mapping from a destination domain to a source domain. The mapped variables can be further defined letting V be a variable defined on the source domain. Then a mapped variable W can be defined on the destination domain by W=V(F).

An embodiment of the integrated variables can be defined by letting V be a variable defined on a d-dimensional domain M in some d-dimensional Euclidean space. The integrated variables can be further defined by letting b<d, and letting P be the projection onto a b-dimensional Euclidean space defined by P(p,y)=p, where p and y are b-tuples and (d−b)-tuples of real numbers, respectively. Here we consider (p,y) as a point in the d-dimensional space. Further assume that the projection of M, P(M), is a domain. Then an integrated variable W can be defined on P(M) in the following way: for each point p in P(M), the value W(p) is defined as the integral of V over the subset of M that is projected onto p by P.

The plurality of variables, as described above, can be combined into any one or more of a plurality of permutations to form other variables. For example, integration along curved domains can be implemented by combining mapped variables and integrated variables. However, it may be clearer if the steps are separated, as described above. In an embodiment, some examples of these combinations of the above variables types, can include Expression variables, Boundary coupled variables, Scalar coupling variables, Extrusion coupling variables and Projection coupling variables, which are each described in detail below.

An embodiment may define Expression variables using a number of disjoint domains that are numbered 1, 2, . . . , n. Let E1, E2, . . . , En be a number of expressions, where Ek is defined on domain number k. Then an expression variable W can be defined on the union of the domains in the following way: W=Ek on domain k, for all k. In this instance, the expression variable can be represented as a glued variable, where the variables that are glued together are auxiliary variables. This is done by introducing names V1, . . . , Vn for the expressions E1, . . . , En. The expression variables are defined in the fields xfem.fem{g}.***.expr, where *** is equ, bnd, edg, or pnt, and g is the geometry number. The expr field is a list of alternating variable names and defining expressions. A defining expression can be substituted with a list of expressions, where the nth expression applies to the nth domain group.

An embodiment may define Scalar coupling variables by defining new variables as expressions of variables, which are evaluated somewhere else. The variable is defined as the integral of an expression over some domains. Such a variable can be defined by the following data that may be included in a data structure and associated fields in an embodiment:

c.elem=elcplscalar;

c.src.g= . . . ;

c.src.equ.var . . . ;

c.src.equ.ind= . . . ;

c.src.bnd.var= . . . ;

c.src.bnd.ind= . . . ;

c.src.edg.var= . . . ;

c.src.edg.ind . . . ;

c.src.pnt.var= . . . ;

c.src.pnt.ind . . . ;

c.dst.g= . . . ;

c.dst.edg.ind= . . . ;

c.dst.bnd.ind= . . . ;

c.dst.edg.ind . . . ;

c.dst.pnt.ind= . . . ;

xfem.elemcp1 {iel} c;

What will now be described are the data fields set forth above. The above described data creates a scalar coupling variable element structure c with index iel with the field c.elem above. The src field defines the new scalar variables in terms of integrals of expressions over geometry src.g (which defaults to 1). Src.equ.var defines variables in terms of integrals over subdomains. Further, src.equ.var is a cell vector with alternating variable names and expressions. The expressions can be numeric constants, strings or cell vector of such. If the expression is a cell vector, then its nth component applies to the nth subdomain group. The subdomain groups are defined by the src.equ.ind field. The default subdomain grouping is that all subdomains are in one group. The variable is defined to have the value obtained by integrating the expression over the subdomain groups. If required, a field src.gporder or src.equ.gporder can be given to specify the order of the quadrature formula to use in numerical integration as described, for example, in Cook, R. D., Malkus, D. S., & Plesha, M. E., Concepts and Applications of Finite Element Analysis, Wiley, 1988 and Zienkiewicz, O. C. & Taylor, R. L., The Finite Element Method, vol. 1, McGraw-Hill, 1994. The order should be a positive integer, and, in one embodiment, the default is 2.

Similarly, src.bnd, src.edg, and src.pnt define scalar variables as integrals over boundaries, edges, and vertices, respectively an integral over a vertex is just the value of the integrand at the vertex). By default, the variables defined in src can be used everywhere in a geometry under analysis. The optional field dst can be used to specify the domains of definition for the variables in detail. Dst.g specifies the geometry number on which the variables are defined (defaults to 1). The dst.***.ind fields specify on which domains the variables are defined.

A variable defined, as described above, may be referred to as a scalar coupling variable. Such a variable can be seen as a combination, for example, of an expression variable, an integrated variable and a mapped variable, as follows. The expressions in src.***.var define an expression variable. The expression variable may be integrated over its domain of definition, producing an integrated variable that is defined on a zero-dimensional space. The integrated variable may be further mapped to the destination domain using the mapping F that sends all points to the point in the zero-dimensional space.

An embodiment may define Extrusion coupling variables by defining new variables as expressions of variables evaluated somewhere else. The Extrusion coupling variables are defined in a source domain and used in a destination domain. The value of the variable at an evaluation point in the destination domain is found by evaluating an expression at a point in the source domain, where the choice of point in the source domain is dependent on the position of the evaluation point in the destination domain.

An extrusion coupling variable can be defined by the following data fields as may be included in a data structure in an embodiment:

c.elem=elcplextr;

c.src.g= . . . ;

c.src.equ.var= . . . ;

c.src.equ.ind= . . . ;

c.src.bnd.var= . . . ;

c.src.bnd.ind= . . . ;

c.src.edg.var= . . . ;

c.src.edgind . . . ;

c.src.pnt.var= . . . ;

c.src.pnt.ind= . . . ,

c.src.meshp= . . . ;

c.dst.g= . . . ;

c.dst.equ.ind= . . . ;

c.dst.bnd.ind= . . . ;

c.dst.edg.ind= . . . ;

c.dst.pnt.ind= . . . ;

c.dst.ep= . . . ;

xfem.elemcpl{iel}=c;

The foregoing fields will now be described in more detail. The above described data creates an extrusion coupling variable element structure c with index iel with c.elem above. The extrusion coupling variables are similar to scalar coupling variables in that the basic fields in dst and src of the element structure are the same. That is to say, that dst defines the geometry and domains, where the variables are available, and src defines the variable names and associated expressions, and the geometry and domains from which they are defined. For extrusion coupling variables, the main difference is that src has a new field meshp, and dst has a new field ep. These describe the way in which an evaluation point in the destination domain is associated with a point in the source domain.

The src field defines the new variables in terms of expressions on geometry src.g (which defaults to 1). Src.equ.var defines variables in terms of expressions on subdomains. Further, src.equ.var is a cell vector with alternating variable names and expressions. The expressions can be numeric constants, strings or cell vector of such. If it is a cell vector, then its nth component applies to the nth subdomain group. The subdomain groups are defined by the src.equ.ind field, and it has the usual syntax. The default subdomain grouping is that all subdomains are in one group. Similarly, src.bnd, src.edg, and src.pnt define variables in terms of expressions on boundaries, edges, and vertices, respectively. In addition, the term dst.g specifies the geometry number on which the variables are defined (defaults to 1). The dst.***.ind fields specify on which domains the variables are defined.

The expressions in src.***.var may be used to define a number of variables, in the same way as expression variables are defined, in which the variables are defined in the source domain. Consider a variable, v 1. What will now be described is how the values of the variable v1 are transferred to the destination domain, thus defining the variable w1 in the destination domain. The field src.meshp as described in more detail elsewhere herein is a cell vector of expressions, one for each space dimension in the source domain. These expressions define the components of a mapping Fs, which maps the source domain into an auxiliary Euclidean space of the same dimension. It is assumed that the inverse of this mapping, Fsi, exists. The inverse Fsi can be computed by search in the image of the source domain mesh under Fs (see Frey, P. J. & George, P.-L., Mesh Generation, application to finite elements, HERMES Science Publishing, 2000, pp. 89-90) and linear interpolation, followed by Newton iteration. Similarly, the field dst.ep may be a cell vector of expressions, where the number of expressions is the same as the dimension of the auxiliary Euclidean space. These expressions define the components of a mapping Fd, which maps the destination domain into the auxiliary space. Now the variable w1 is defined on the destination domain by the formula w1(p)=v1(Fsi(Fd(p))), where p denotes points in the destination domain. The variable w1 may be referred to as an extrusion coupling variable. Based on the foregoing, w1 may be obtained as a combination of an expression variable and mapped variables. Namely, first the expression variable v1 is created. Then v1 is mapped to the auxiliary space using the mapping Fsi resulting in a mapped variable in the auxiliary space. Then this is further mapped to the destination domain using the mapping Fd producing a mapped variable, such as w1.

In an embodiment, Projection coupling variables may be defined as line integrals of expressions evaluated somewhere else. The variables are defined in a source domain and used in a destination domain. The value of the variable at an evaluation point in the destination domain is found by evaluating a line integral of an expression at in the source domain, where the choice of line (curve) in the source domain is dependent on the position of the evaluation point in the destination domain.

A projection coupling variable may be defined using the following fields included in a data structure in an embodiment:

c.elem=elcplproj;

c.src.g= . . . ;

c.src.equ.var= . . . ;

c.src.equ.ind= . . . ;

c.src.bnd.var . . . ;

c.src.bnd.ind= . . . ;

c.src.meshp= . . . ;

c.dst.g= . . . ;

c.dst.equ.ind= . . . ;

c.dst.bnd.ind= . . . ;

c.dst.edg.ind= . . . ;

c.dst.pnt.ind= . . . ;

c.dst.ep= . . . ;

xfem.elemcpl{iel}=c;

The foregoing data fields will now be described in more detail. The above described data defines a projection coupling variable element structure c with index iel with c.elem as defined above. Projection coupling variables are similar to elcplscalar in that the fields included in dst and src of the element structure are the same. In other words, dst defines the geometry and domains where the variables are available, and src defines the variable names and associated expressions, and the geometry and domains from which they are defined. For projection coupling variables, the main difference is that src has a new field meshp, and dst has a new field ep. These describe the way in which an evaluation point in the destination domain is associated with points in the source domain. The fields meshp, and ep are similar to elcplextr, with a few small changes.

The src field defines the new variables in terms of expressions on geometry src.g (which defaults to 1). Src.equ.var defines variables in terms of expressions on subdomains. It is a cell vector with alternating variable names and expressions. The expressions can be numeric constants, strings or cell vector of such. If it is a cell vector, then its nth component applies to the nth subdomain group. The subdomain groups are defined by the src.equ.ind field, and it has the usual syntax. The default subdomain grouping is that all subdomains are in one group. Similarly, src.bnd, src.edg, and src.pnt define variables in terms of expressions on boundaries, edges, and vertices, respectively.

Dst.g specifies the geometry number on which the variables are defined (defaults to 1). The dst.***.ind fields specify on which domains the variables are defined. They have the usual syntax.

The expressions in src.***.var may be used to define a number of variables, in the same way as expression variables are defined, in the source domain. Consider one of these variables v1. What will now be described is how the values of the variable v1 may be transferred to the destination domain, thus defining the variable w1 in the destination domain. The field src.meshp is a cell vector of expressions, one for each space dimension in the source domain and may be used in defining the components of a mapping Fs, which maps the source domain into an auxiliary Euclidean space of the same dimension. It is assumed that the inverse of this mapping, Fsi, exists. The inverse Fsi may be computed by searching in the image of the source domain mesh under Fs (see Frey, P. J, & George, P.-L., Mesh Generation, application to finite elements, HERMES Science Publishing, 2000, pp. 89-90) and linear interpolation, followed by Newton iteration. A temporary variable, v2, may be defined in the auxiliary space by the formula v2(p)=v1(Fsi(p)), where p denotes points in the auxiliary space. The field dst.ep may be a cell vector of expressions, where the number of expressions is one less than the dimension of the auxiliary Euclidean space in which the expressions define the components of a mapping Fd, which maps the destination domain into a subspace of the auxiliary space. This subspace is defined as the subspace in which the last coordinate is zero. Define a further variable v3 on this subspace as the integrated variable obtained from v2 by integration along lines orthogonal to the subspace. Finally, the variable w1 is defined on the destination domain by the formula w1 (p)=v2(Fd(p)), where p denotes points in the destination domain. Based on the foregoing, the variable w1 may be referred to as a projection coupling variable. Also based on the foregoing, w1 may be obtained as a combination of an expression variable (v1), a mapped variable (v2), an integrated variable (v3), and a mapped variable (w1).

An embodiment can define Boundary coupled variables on boundaries in the following manner. Given is an expression E defined on a subdomain. Then a Boundary coupled variable W can be defined by W=E on a boundary that touches this subdomain. Thus a Boundary coupled variable is a special case of a mapped variable (of an auxiliary variable), where the mapping F is the identity mapping from a boundary into an adjacent subdomain. Optionally, one can start with two expressions Eu and Ed that are defined on the two adjacent subdomains to a boundary, respectively. Then a Boundary coupled variable W can be defined on the boundary as W=(Eu+Ed)/2. In this case, W is the mean value of two mapped variables. The data structure that defines Boundary coupled variables can have the form

c.elem=elcplbnd; /** this represents the boundary coupled variable type of structure */

c.g=g;

c.bnd.vara=varu;

c.bnd.vard=vard;

c.bnd.varm=varm;

c.bnd.ind−ind;

xfem.elemcpl{i}=c;

where the foregoing fields are described in following paragraphs. The above creates a boundary coupled variable element structure c with index i. The variable definitions given by varu, vard, and varm will be active only in geometry number g. If the ind field is given, the definitions will apply only in the specified boundary groups. Varu, yard, and varm are cell vectors

{varname1 expr1 varname2 expr2 . . . }

with alternating variable names and defining expressions. The expressions can be numerical constants, strings, or cell vectors of numerical constants and strings. In the case of a cell vector, its nth component applies to the nth group of boundaries given by ind (dm ind field is not given, the first entry of the cell vector applies to all boundaries). Otherwise, the expression applies to all boundary groups.

For varu and vard, the value of the variable is the expression evaluated in the upper/lower subdomain, or zero if there is no upper/lower subdomain. For varm, the value is the mean of the upper and lower values on an inner boundary, the adjoining value on an outer boundary, and NaN if there is no subdomain on either side.

An embodiment of the method may further include a scheme for numerical computation of the values of a variable in accordance with each type as one of a basic variable, an auxiliary variable, a glued variable, a mapped variable, and an integrated variable. For example, assume that a user wants to compute the values of the variable Win the points p1, p2, . . . , pm, given values Ui for the DOFs. The points pj are specified by giving the values of the local coordinates, and the mesh elements in which they reside. The result can be represented as a row vector, where the jth component is W(pj). Depending on what type of variable W is, there are five possible cases, e.g., W is a basic variable, W is an auxiliary variable, W is a glued variable, W is a mapped variable and W is an integrated variable, which are described in detail below. If W is a basic variable, its values can be computed directly. If W is any of the other types of variables, the values of the variables occurring in the definition of W should first be computed. Thus, a recursive scheme is set forth for computation of the values.

In the case where W is a basic variable, as described above, W is the sum of Ui*Fi over all indices i. Values are given by W(pj)=sum of Ui*Fi(pj) over all i. Since pj is given in local coordinates, and Fi is a polynomial, it is easy and well known how to evaluate Fi(pj).

In the case where W is an auxiliary variable, W=E(V1, V2, . . . , Vn), as described above, the values of the variables V1, V2, . . . , Vn in the points pj are determined. The values of W may then be computed as W(pj)=E(V1(pj), V2(pj), . . . , Vn(pj)), by evaluating this expression. Note: if the expressions are parsed on the fly, it is wise to carry out the evaluation on a large set of points in parallel, in order to save computation time.

In the case where W is a glued variable, W(pj)=Vk(pj) for those points pj, which are in domain k, as described above. For each k, let the vector Ik contain the indices j of the points pj that lie in domain k. First compute the values of the variables V1, V2, . . . , Vn. In other words, compute the values of the variable Vk in the points pj, where j is in Ik. Subsequently, define W(pj)=Vk(pj) for j in Ik.

In the case where W is a mapped variable, W(pj)=V(qj), where qj are the points qj=F(pj), as described above. These points are computed in the following way: First, the global coordinates for the points pj are computed, and the global coordinates for the points qj are computed by the formula qj=F(pj). Then, a search algorithm may be used to find the mesh elements in which the points qj reside in, and the corresponding local coordinates. Such search algorithms are known to those of ordinary skill in the art, for example, at pages 89-90 of “Mesh Generation Application to Finite Elements” by Frey et al. also referenced elsewhere herein. Subsequently, the variable V is computed in the points qj. The result is identical with the requested values, namely the values of W in the points pj.

In the case where W is an integrated variable, W(pj) is the integral of V(pj,y) over all y such that (pj,y) lies in the domain of V, as described elsewhere herein. This integral is approximated with a quadrature formula in the standard way, i.e., W(pj) is approximated with the sum of V(pj,yjk)*wjk over some indices k (the index set can depend on j), see for example, Zienkiewicz, O. C. & Taylor, R. L., The Finite Element Method, vol. 1, McGraw-Hill, 1994. The numbers wjk are called the weights. Let q1, q2, . . . be the points (pj,yjk) in some order, and let w1, w2, . . . be the corresponding ordering of the weights wjk. Create the index vector J in the following way: J(1) is the index j for which q1=(pj,yjk) (for some k). Thus J maps from indices of the points q1, q2, . . . to indices of the projected points pj. Now compute the values of the variable V in the points q1, q2, . . . . The result is represented by a row vector R. The values for the variable W can be now be computed as follows. W(pj)=sum of R(1)*w(1), where the sum is taken over all 1 such that J(1)=j.

An embodiment may also include a format for numerical representation of the Jacobian of a variable. The Jacobian of a variable V may be defined as the vector consisting of the first partial derivatives of V with respect to the DOFs, denoted as a vector U=[U1, . . . Un] where n is the number of DOFs. The partial derivative of V with respect to Ui is denoted DiV. Assume that we want to evaluate the Jacobian of V in a number of points p1, p2, . . . , pm. The Jacobian of V in these points can be represented by a number of contributions J1, J2. The number of contributions used in computing the Jacobian of a variable may vary in accordance with each variable's type and complexity. It should be noted that in the following description, the references to VAL, DOF and EP are variables used and referenced elsewhere herein in processing steps when computing the Jacobian. Each contribution Jk consists of three things: A matrix Jk.VAL, a matrix Jk.DOF, and a row vector Jk.EP. For a fixed index k, the matrices Jk.VAL and Jk.DOF have the same size, and they have the same number of columns as Jk.EP. The DOF matrix contains degree of freedom indices, and the VAL matrix contains the corresponding contributions to the value of the partial derivative. The EP vector contains evaluation point indices. More precisely, this means that the partial derivative DiV(pj) is equal to the sum of Jk.VAL(r,c), where the sum is taken over all k, r, and c such that Jk.D0F(r,c)=i and Jk.EP(c)=j. Note that r and c denote the row and column indices, respectively, in the matrices. Often, the vector Jk.EP is [1 2 . . . m]. In order to conserve memory space, the EP vector can be omitted in this case.

It should be noted that the Jacobian of a variable with respect to the degrees of freedom should not be confused with the stiffness matrix described elsewhere herein in which the stiffness matrix is the Jacobian matrix of the residual with respect to the degrees of freedom.

The points p1, p2, . . . , pm may be uniformly distributed in the mesh elements. In other words, the first b points lie in the first mesh element, the next b points lie in the second mesh element, etc. In this case, the local coordinates may also be the same in all mesh elements. This type of local point data may be referred to as structured point data, and the general case is called unstructured point data. For a basic variable, structured point data means that the matrices Jk.DOF can be compressed. Namely, the first b columns of Jk.DOF are identical, the next b columns of Jk.DOF are identical, etc. A more compact format can be realized by keeping only every bth column of Jk.DOF. This compact format can be preserved as long as only basic variables, auxiliary variables, and glued variables are used. In using “structured” data, element coordinates for the evaluation points are the same for all mesh elements. With unstructured point data, element coordinates are specified for each evaluation point individually.

Additionally, an embodiment may also include a scheme for a numerical computation of the Jacobian of a variable. Assume that it is desired to compute the Jacobian of a variable W in the points p1, p2, . . . , pm, given values for the DOFs Ui. The points pj are specified by giving the values of the local coordinates, and the mesh elements in which they reside. The result can be represented in the format described above. Depending on what type of variable W is, there are five possible cases, e.g. W is a basic variable, W is an auxiliary variable, W is a glued variable, W is a mapped variable or W is an integrated variable, which are discussed in detail below. If W is a basic variable, the Jacobian can be computed directly. If W is any of the other types of variables, the Jacobians of the variables occurring in the definition of W must first be computed. Thus, a recursive scheme is set forth for computation of the Jacobian.

In the case where W is a basic variable, recall that W is the sum of Ui*Fi over all indices i. Thus, the partial derivatives are DiV(pj)=Fi(pj). The Jacobian can represented with just one contribution J1. The vector J1.EP may be represented as a vector [1 2 3 . . . m]. Consider the mesh element in which the point pj lies. Only a few basis functions are nonzero on this mesh element. The indices i of these basis functions constitute the jth column of the matrix J1.D0F. The corresponding values Fi(pj) make up the jth column of the matrix J1.VAL. Since pj is given in local coordinates, and Fi is a polynomial, it is easy and well known how to evaluate Fi(pj).

In the case where W is an auxiliary variable, recall that W=E(V1, V2, . . . , Vn). By the chain rule,

${D_{1}{W\left( p_{j} \right)}} = {\sum\limits_{k}^{\;}{\frac{\partial E}{\partial V_{k}}\left( p_{j} \right)D_{i}{{V_{k}\left( p_{j} \right)}.}}}$

First compute the Jacobians of the variables Vk, k=1, 2, . . . , n. These are represented by the contributions Jkl, for each variable “k” having one or more “l” contributions (where the index 1 can run over different sets for the different k). Compute the partial derivatives of E symbolically, for example, as described in Davenport, J. H., Siret, Y. & Tournier, E., Computer Algebra, systems and algorithms for algebraic computation, Academic Press, 1993, and evaluate the partial derivatives in the points pj, using the algorithm described above. Store the result in the vectors Ck:

${C_{k}(j)} = {\frac{\partial E}{\partial V_{k}}\left( p_{j} \right)}$

Now the Jacobian of W can be represented by the contributions Kkl, which are computed as follows. The EP and DOF matrices are the same as for the variables Vk: Kkl.EP=Jkl.EP and Kkl.DOF=Jkl.DOF. The VAL matrices are computed as follows: KkI.VAL(r,c)=Ck(Jkl.EP(c))*Jkl.VAL(r,c). The calculated contributions Kkl should then be reindexed in terms of just one index.

In the case where W is a glued variable, recall that W(pj)=Vk(pj) for those points pj which are in domain k. For each k, let the vector Ik contain the indices j of the points pj that lie in domain k. First compute the Jacobians of the variables V1, V2, . . . , Vn. More precisely, compute the Jacobian of the variable Vk in the points pj, where j is in Ik. This Jacobian is represented by the contributions Jkl (where the index 1 can run over different sets for the different k). Now the Jacobian of W can be represented by the contributions Kkl, which are computed as follows. The VAL and DOF matrices are unchanged: Kkl.VAL=Jkl.VAL and Kkl.DOF=Jkl.DOF. Kkl.EP is obtained from Jkl.EP by KkI.EP=Ik(Jkl.EP). The calculated contributions Kkl should then be reindexed in terms of just one index.

In the case where W is a mapped variable, recall that W(pj)=V(F(pj)). Thus, the partial derivatives are DiW(pj)=DiV(qj), where qj are the points qj=F(pj). These points are computed in the following way: first, the global coordinates for the points pj are computed, and the global coordinates for the points qj are computed by the formula qj=F(pj). Then, a search algorithm is used to find the mesh elements in which the points qj reside in, and the corresponding local coordinates. Now the Jacobian of the variable V can be computed in the points qj. The result is identical with the requested Jacobian, namely the Jacobian of W in the points pj.

In the case where W is an integrated variable, recall that W(pj) is the integral of V(pj,y) over all y such that (pj,y) lies in the domain of V. This integral is approximated with a quadrature formula in the standard way, i.e., we approximate W(pj) with the sum of V(pj,yjk)*wjk over some indices k (the index set can depend on j). Thus, the partial derivative DiW(pj) can be obtained as the sum of DiV(pj,yjk)*wjk over k. Let q1, q2, . . . be the points (pj,yjk) in some order, and let w1, w2, be the corresponding ordering of the weights wjk. Create the index vector J in the following way: J(1) is the index j for which q1=(pj,yjk) (for some k). Thus, J maps from indexes of the points q1, q2, . . . to indices of the projected points pj. Now the Jacobian for the variable V can be computed in the points q1, q2, . . . . The result is represented by the contributions Jk. The Jacobian for the variable W can be represented by the contributions Kk, which are computed as follows. The DOF matrices are unchanged, Kk.DOF=Jk.DOF. The VAL matrices are transformed according to Kk.VAL(r,c)=Jk.VAL(r,c)*wc. The new EP vectors are constructed by Kk.EP(c)=J(Jk.EP(c)).

An embodiment may also provide an optimization using a cache, for example, when using the above recursive algorithms for computing values and Jacobians of variables, it often happens that one computes the same variable several times at different levels of the recursion tree. To save computing time, the results of the evaluations may be stored in the cache data structure for later use. In the cache, each result is stored together with a key, which identifies which variable was evaluated, and whether it was values or the Jacobian that was computed. To search among the keys, hashing can be used. It is important also to keep track of the evaluation points. Each time one switches from one set of evaluation points to another set, one must make sure that either the cache is cleared, or, that the cache is pushed. In the latter case the cache works as a stack where each level corresponds to a set of evaluation points. When a user is done with one set of evaluation points, the user can return to the previous set by popping the cache.

An embodiment may further include assembling the residual vector of a weak equation. For example, consider a weak term, that is, an expression of the type V_test*W, where V and W are variables. The residual vector L corresponding to the weak term is a column vector defined by L(r)=integral of DrV*W over some domain; where we have assumed some given values of the DOFs Ui. To compute the residual vector numerically, we approximate this integral with a quadrature formula: L(r)=sum of DrV(pj)*W(pj)*wj over certain indices j=1, 2, . . . , m. Thus, the method may begin by computing the Jacobian of V and the values of W in the points pj using the above methods. Assume that the Jacobian of V in the points pj is represented by the contributions Jk. For simplicity, assume that the variable V is constructed from basic variables, only using auxiliary variables. Thus, the contributions Jk all have Jk.EP=[1 2 . . . m]. Compute the row vector C as C(j)=W(pj)*wj. Now the residual vector L can be computed as follows: start with L as the zero vector. Loop over all k, then over all columns j of Jk.DOF, and then over all rows r of Jk.DOF, and add Jk.VAL(r,j)*C(j) to L(Jk.DOF(r,j)).

It should be noted that a weak term can in general have the form V_test*E(V1, V2, . . . , Vn). To simplify the presentation, a name W can be introduced for the expression E(V1, V2, . . . , Vn), which is possible by using an auxiliary variable. V_test is described elsewhere herein in more detail.

A weak expression may be defined as a sum of weak terms. A weak equation is obtained by summing a number of integrals of weak expressions, and putting the result equal to zero. FIG. 41 shows the weak formulation. The integrals can be taken over different domains. Partial differential equations can be reformulated as weak equations.

FIG. 42 describes the conversion from a general form problem to a weak form. A weak equation is the starting point for the finite element method. Therefore, it is important to be able to compute the residual vector corresponding to a weak equation. The residual vector can be obtained as the sum of the residual vectors of the underlying weak terms. The stiffness matrix corresponding to a weak equation is the Jacobian of its residual vector. Therefore, the stiffness matrix can be computed as the sum of the stiffness matrices of the underlying weak terms. Computation of the stiffness matrix is discussed in further detail below.

An embodiment may further include assembling the stiffness matrix of a weak equation. For example, consider a weak term, that is, an expression of the type V_test*W, where V and W are variables. The stiffness matrix S corresponding to the weak feint is defined by S(r,c)=integral of DrV*DcW over some domain. To compute the stiffness matrix numerically, an approximation is made of this integral with a quadrature formula: S(r,c)=sum of DrV(pj)* DcW(pj)*w(j) over certain indices j=1, 2, . . . , m. Thus, the method of assembling the stiffness matrix of a weak equation is commenced by computing the Jacobians of V and W using the above method. Assume that these Jacobians are represented by the contributions J1 and Kk, respectively. For simplicity, assume that the variable V is constructed from basic variables, only using auxiliary variables. Thus, the contributions J1 all have J1.EP=[1 2 . . . m]. Now form the matrices COLk, ROWlk, and the three-dimensional arrays VALlk as follows. Put COLk=Kk.DOF and ROWlk(r,c)=J1.DOF(r,Jk.EP(c)). The array VALlk is defined by VALlk(r,c,s)=J1.VAL(r,Jk.EP(s))*Kk.VAL(c,s)*w(Jk.EP(s)). Now the arrays COLk, ROWlk, and VALlk constitute a kind of sparse matrix representation of S. More precisely, S(r,c)=sum of VALlk(i,j,s), where the sum is taken over all l, k, s, i, and j such that r=ROWlk(i,s) and c=COLk(j,s).

An embodiment may further include assembling the constraints of a weak equation. For example, consider a constraint W=0 on some domain, where W is a variable. The constraint is discretized by requiring that W=0 holds in a finite number of points pj, j=1, 2, . . . , m. Often, the points pj are uniformly distributed in each mesh element on the domain. The constraint residual vector M is defined as the column vector with the components Mj=W(pj). This vector can be computed with the method for evaluating the variable W described above.

The constraint matrix C is the Jacobian of M with respect to the degrees of freedom, namely, Cji=DiMj=DiW(pj). The constraint matrix C can be computed by computing the Jacobian of W in the points pj using the method described above. The result is a list of contributions Jk. Now the partial derivative DiW(pj) can be computed as the sum of Jk.VAL(r,c), where the sum is taken over all k, r, and c such that Jk.DOF(r,c)=i and Jk.EP(c)=j.

In understanding the assembly and solution process, it is helpful to understand how the discretization of a stationary PDE problem is formed. The starting point is the weak formulation of the problem in FIG. 41 and then with the discretization of the constraints:

0=R ⁽²⁾ on Ω

0=R ⁽¹⁾ on B

0=R ⁽⁰⁾ on P

The constraints on subdomains, boundaries, and vertices are stored in the sub-fields equ.constr, bnd.constr, and pnt.constr, respectively, of xfem.fem{g}. Consider the constraints on boundaries B. For each mesh element in B (i.e., mesh edge in B), consider the Lagrange points of some order k (i.e., the points whose local coordinates are a multiple of 1/k). Denote them by x(1)mj, where m is the index of the mesh element. Then the discretization of the constraint is

0=R ⁽¹⁾(x ⁽¹⁾ _(mj))

-   -   that is, the constraints are required to hold point-wise, at the         Lagrange points. The Lagrange point order k can be chosen         different for different components of the constraint vector         R⁽¹⁾, and it can also vary in space (this is determined by the         field xfem.fem {g}.bnd.cporder). The k is denoted by cporder         that may be included in a data structure described elsewhere         herein. The constraints on subdomains W and points P are         discretized similarly (nothing needs to be done with the points         P). We can collect all these point-wise constraints in one         equation 0=M, where M is the vector consisting of all the         right-hand sides.

The dependent variables are approximated with functions in the chosen finite element space(s). This means that the dependent variables are expressed in terms of the degrees of freedom as

$u_{l} = {\sum\limits_{i}^{\;}{U_{i}\phi_{i}^{(1)}}}$

where phi₁ ⁽¹⁾ are the basis functions for variable u₁. Let U be the vector with the degrees of freedom U_(i) as the components. This vector is called the solution vector, since it is what is to be computed. Now M only depends on U, so the constraints can be written 0=M(U). Now consider the weak equation:

$0 = {{\int_{\Omega}^{\;}{W^{2}\ {A}}} + {\int_{B}^{\;}{W^{(1)}\ {s}}} + {\sum\limits_{P}^{\;}W^{(0)}} - {\int_{\Omega}^{\;}{{v \cdot h^{{(2)}\Gamma}}\ \mu^{(2)}{A}}} - {\int_{B}^{\;}{{v \cdot h^{{(1)}\Gamma}}\ \mu^{(1)}{s}}} - {\int_{P}^{\;}{{v \cdot h^{{(0)}\Gamma}}\ \mu^{(0)}}}}$

The integrands W(2), W(1), and W(0) are stored in the subfields equ.weak, bnd.weak, and pnt.weak, respectively, of xfem.fem{g}. The integrands W(2), W(1), and W(0) are weak expressions. To discretize this equation, we express the dependent variables in terms of the DOFs as above. Similarly, the test functions are approximated with the same finite elements (this is the Galerkin method):

$v_{l} = {\sum\limits_{i}^{\;}{V_{i}\phi_{i}^{(1)}}}$

Since the test functions occur linearly in the integrands of the weak equation, it is enough to require that the weak equation holds when we choose the test functions as basis functions:

ν_(l)=φ_(i) ⁽¹⁾

When substituted into the weak equation, this gives one equation for each i. Now the Lagrange multipliers have to be discretized. Let

Λ_(mj) ^((d))=μ^((d))(χ_(mj) ^((d)))w _(mj) ^((d))

where x(d)mj are the Lagrange points define above, and w(d)mj are certain weights, see below. The term

∫_(B) ϕ_(i) ⋅ h^((1)Γ) μ⁽¹⁾s

is approximated as a sum over all mesh elements in B. The contribution from mesh element number m to this sum is approximated with the Riemann sum

${\sum\limits_{j}{{{\phi_{i}\left( x_{mj}^{\lbrack 1\rbrack} \right)} \cdot {h^{{\lbrack 1\rbrack}T}\left( x_{mj}^{(1)} \right)}}{\mu^{(1)}\left( x_{mj}^{(1)} \right)}w_{mj}^{(1)}}} - {\sum\limits_{j}{{{\phi_{i}\left( x_{mj}^{(1)} \right)} \cdot {h^{{(1)}T}\left( x_{mj}^{(1)} \right)}}\Lambda_{mj}^{(1)}}}$

where w(l)mj is the length (or integral of ds) over the appropriate part of the mesh element. The integral over W and the sum over P is approximated similarly.

All this means that the discretization of the weak equation can be written

0=L−N ^(Γ)Λ

L is the vector whose ith component is

${\int_{Q}{W^{(2)}{A}}} + {\int_{B}{W^{(1)}{s}}} + {\sum\limits_{P}W^{(0)}}$

-   -   evaluated for vl,=phi(l)i. LAMBDA is the vector containing all         the discretized. Lagrange multipliers LAMBDA(d)mj. N is a matrix         whose ith column is a concatenation of the vectors

h ^((d))(χ_(mj) ^((d)))φ₁(χ_(mj) ^((d)))

To sum up, the discretization of the stationary problem is

0=L(U)−N(U)^(T)Λ

0=M(U)

The objective is to solve this system for the solution vector U and the Lagrange multiplier vector LAMBDA. L is called the residual vector, M is the constraint residual vector and C=−N is the constraint matrix. Note that M is redundant in the sense that some point wise constraints occur several times. Similarly, L is redundant. This redundancy is removed by the solvers. The solution of the discrete system is obtained by using Newton's iterative method, i.e. by solving a number of linearized problems (see below).

The integrals occurring in the components of the residual vector L (as well as the stiffness matrix S) are computed approximately using a quadrature formula. Such a formula computes the integral over a mesh element by taking a weighted sum of the integrand evaluated in a finite number of points in the mesh element. The order of a quadrature formula is the maximum number k such that it integrates all polynomials of degree k exactly. Thus, the accuracy of the quadrature increases with the order. On the other hand, the number of evaluation points also increases with the order. As a rule of thumb one can take the order to be twice the order of the finite element that is used. The order of the quadrature formula is denoted by gporder in the data structures (gp stands for Gauss points).

In time-dependent problems, the discretization of a time-dependent problem is similar to the stationary problem:

${{D\left( {U,t} \right)}\frac{U}{t}} = {{L\left( {U,t} \right)} - {{N\left( {U,t} \right)}^{T}\Lambda}}$ 0 − M(U, t)

where now U and LAMBDA depend on time t. The matrix D is called the mass matrix. This matrix is assembled in a similar way as the stiffness matrix, but from data in the fields xfem.fem{g}.***.dweak instead of xfem.fem{g}.***.weak. It is assumed that the constraint is linear, i.e., M depends linearly on U. The solution of the above system of differential-algebraic equations can be obtained by using standard DAE-solvers.

In considering a linearized stationary problem, the linearization “point” corresponds to a solution vector U₀. The discretization of the linearized problem is

K(U ₀)(U−U ₀)+N(U ₀)^(Γ) Λ=L(U ₀)

N(U ₀)(U−U ₀)=M(U ₀)

where S=−K is called the stiffness matrix. The solution of this linear system can be obtained by standard direct or iterative methods.

In Eigenvalue problems, the discretization of the eigenvalue problem is

λD(U ₀)U+K(U ₀)U+N(U ₀)^(Γ)Λ=0

N(U ₀)U=0

where U₀ is the solution vector corresponding to the linearization “point”. The solution to this eigenproblem can be obtained by standard methods.

Referring now to FIG. 36, shown is an example of another embodiment of a user interface or GUI 600 that may be used in connection with specifying local and non-local couplings of multiphysics systems. The GUI 600 is similar in features and operation as the GUI 30 of FIG. 3 and further includes an option to add geometries, which is discussed in detail below. On the GUI 600, a user can start a multiphysics model that consists of several application modes and several different geometries. The user can start in the top left part of the GUI 600 by specifying space dimension (1-D, 2-D, or 3-D) and the user can elect to edit the names of the independent variables in the Independent variables dialog box 602. The user can also select application modes from the left-most list box 604 and add them to the model by pressing the >> button 606 or by double-clicking them. Application modes can be removed from the list by pressing << button 608 or double-clicking on them. When the last application mode is removed from a geometry, the geometry is still left in the right list box 610. This corresponds to a geometry only model where you can draw a geometry and then add application modes later on. The user can also press the << button 608 once more to remove the geometry. There is always one geometry available in the right list box 610. A user can add additional geometries to the model by pressing the >> button 612 a after selecting from the Geometry name drop-down list box 614 (the Add button 612 changes to a >> button 612 a after clicking it, and thus adds geometry to the Geometry name drop-down list box 614). Each geometry can also have a different space dimension.

Prior to the user adding an application mode, as described above, the user can edit the name of the application mode. Additionally, the user can also edit the name of the application mode's dependent variables and the element type used for modeling. Each application mode in the model is given a unique name, which is used to identify the origin of the variables in the multiphysics model. The user can edit the dependent variables' names, but the names are required to be valid variable names (e.g., they are required to start with a letter). If the application mode contains more than one dependent variable, the user can enter all of the variable names as space-separated entries in the Dependent variables edit field 616. In the PDE modes, where more than one dependent variable is possible, the user can determine the number of equations in the model by entering one or more space-separated variable names.

In the Element drop-down list box 618, the type of element used for the modeling is selected. Each application mode has a set of predefined elements. The element selection of the Element drop-down list box 618 can also be changed during the modeling process using the Element page 802 in the Subdomain Settings dialog box 800 (FIG. 38).

On the right-hand side of the GUI 600 of FIG. 36, a user can set the solver type (stationary, time-dependent, etc.) and solution form (coefficient, general, or weak form) for the multiphysics model by respectively selecting a solver type from the solver type of drop-down list 620 and selecting a solution from the Solution form drop-down list 622. In the list box 610 located below the solution form drop-down list 622, all the application modes that have been added to the model appear. The name and the dependent variables for the selected application mode are displayed below the list box 610. A user can select any of the model's application modes and change its submode by selecting from the elements listed in the Submode drop down list 624. In addition to the Standard submode displayed in the Submode drop-down list 624 of the GUI 600, for example, there is also a Wave-Extension submode (not shown) for some application modes. The Wave-Extension submode extends the standard time-dependent equation to a wave equation (using a second derivative with respect to time). Pressing OK 626 starts a new multiphysics model with all the added application modes, as described above. The application mode that is selected in the right list box 610 becomes the active application mode when the user continues the modeling.

Referring to FIG. 37, shown is an example Boundary settings dialog box 700 that provides a user the ability to access the weak form. In the Boundary settings dialog box 700, a user can enter weak, dweak, and constr coefficient information in the respective weak 702, dweak 704, and constr 706 fields corresponding to the fields xfem.fem{g}.bnd.weak, xfem.fem{g}.bnd.dweak, and xfemSem{g}.bnd.constr, respectively, in the data structure. The dialog box also sets the domain grouping xfem.fem{g}.bnd.ind. The Boundary settings dialog box 700 further includes a Domain selection list 708 that permits a user to select domain related information associated with the weak solution form. The Boundary settings dialog box 700 can also be made available in coefficient view, and also directly in the application mode, for PDE oriented application modes.

Referring to FIG. 38, shown is an example of a Subdomain Settings dialog box 800, which enables a user thereof to set shape function object, integration order, and constraint order, corresponding to the fields xfem.fem{g}.equ.shape, xfem.fem {g}.equ.gporder, and xfem.fem{g}.equ.cporder, respectively, in the data structure. The dialog box also sets the domain grouping xfem.fem {g}.equ.ind. The shape function object, integration order, and constraint order data structures are defined below. In a typical application mode, the element type is only set on a subdomain level, but can be modified in coefficient view, boundary level, edge level, and point level. It is possible that an application mode has no subdomain extent, and thus is defined only on a boundary level and/or below. Then, in one implementation, for example, the application mode can set element types on a boundary level and allow modification of coefficient on edge level and point level.

Referring to FIG. 39, shown is another example of a Subdomain Settings dialog box 900, which permits a user to enter weak, dweak, and constr coefficient information for respective weak 902, dweak 904, and constr 906 fields corresponding to the subfields of the xfem.fem{g} data structure. The dialog box 900 may also be used to specify domain groupings, for example, stored in the xfem.fem{g}.equ.ind field. The dialog box can be made available in coefficient view, and also directly in the application mode, for PDE oriented application modes.

Referring to FIG. 40, shown is an example of a representation of the data structure 1000 that may be included in an embodiment in connection with storing data in connection with the PDEs selected and combined. The data in the data structure 1000 may include data used in connection with the multiphysics model, which is associated with local and/or non-local coupling variables.

The data structure 1000 can include the following fields:

Data field Description fem.mesh Finite element mesh fem.appl {i} Application mode I fem.app1{i}.dim Dependent variable name fem.appl { i } Domain physical data .equ fem.appl {i}.bnd Boundary physical data fern.appl Text string containing submode setting {i}.submode fem.appl {i} Border on or off .border fem.appl {i} Matrix of subdomain usage .usage fem.dim Multiphysics dependent variable names fem.equ PDE coefficients fem.bnd Boundary conditions fem.border Vector of border on or off fem.init Initial value fem.sol Finite element solution fem.sshape Geometry approximation order fem.shape Shape functions fem.expr Definition of variables as expressions fem.equ Variables, equations, constraints, and initial values on subdomains fem.bnd Variables, equations, constraints, and initial values on boundaries fem.edg Variables, equations, constraints, and initial values on edges fem.pnt Variables, equations, constraints, and initial values on vertices

As previously described, the data structure 1000 above can be extended for use with multiple geometries by storing the above data structure for geometry g in a list entry xfem.fem{g}

The data structure 1000 is similarly constructed and arranged as the data structure 250, as described above, and further includes the additional fields: fem.sshape 280, fem.shape 282, fem.expr 284, fem.equ 286, fem.bnd 288, fem.edg 290 and fem.pnt 292, as described above. The global coordinates are polynomials in the local element coordinates of a certain degree k. This degree k can be specified in the field fem.sshape 280. For instance, fem.sshape=2; uses quadratic shape functions for the global space coordinates. This makes it possible for the mesh elements at the boundary to be curved, and thus come closer to the true geometric boundary. The default k is equal to the maximum order of the shape function objects in fem.shape 282, where k is called the geometry shape order. The field fem.shape 282 is a cell vector with shape function objects. For example, fem.shape={shlag(1,‘u’) shlag(2,‘u’) shvec(‘A’)}; defines three shape function objects. A user can choose on which domains these objects will be active, by using the fields fem.equ.shape, fem.bnd.shape, fem.edg.shape, fem.pnt.shape, as discussed in detail below.

In the fields fem.equ.shape, fem.bnd.shape, fem.edg.shape, and fem.pnt.shape, a user can specify where the shape function objects in fem.shape are to be used. For example, fem.shape={shlag(1,‘u’) shlag(2,‘u’) sharg_(—)2_(—)5(‘v’)}; fem.equ.shape={[1 3] [2 3] [ ] 3}; means that on the first subdomain group, only the first and third shape function objects (shlag(1,‘u’) and sharg_(—)2_(—)5(‘v’)) are active. On the second subdomain group, the second and third shape function objects are active. On the third subdomain group, no shape function objects are defined, while on the fourth subdomain group only sharg_(—)25(‘v’) is active. Thus, the variable u will be defined on subdomain groups 1 and 2, having linear elements in subdomain group 1, and quadratic elements in subdomain group 2. If these subdomains groups are adjacent, this will cause problems since “hanging nodes” can appear. Thus, the user should not mix elements for the same variable in adjacent subdomains. If the field fem.equ.shape is not given, then all shape function objects in fem.shape 282 apply in all subdomain groups.

Similarly, the field fem.bnd.shape is a cell vector, which specifies for each boundary group which shape function objects are active. If fem.bnd.shape is not given, then it is inherited from fem.equ.shape. This means that a shape function object, which is active in a subdomain, is also active on the boundary of that subdomain (as well as boundaries lying within the subdomain).

In 3-D, the field fem.edg.shape similarly specifies the usage of shape function objects on edge groups. If the usage of shape function objects is not given, it is inherited from the usage on subdomains and boundaries. That is, a shape function object which is active on some subdomain or some boundary, is also active on all edges that touch this subdomain or boundary. In 2-D and 3-D, the field fem.pnt.shape similarly specifies usage on vertices. Specifying usage on vertices is defaulted by inheritance from subdomain, boundaries, and edges.

The fields fem.usage and fem.border mentioned earlier can be implemented in terms of the fem.***.shape fields by not assigning a shape function object to a subdomain, boundary, edge or point. Thus with the fields fem.***.shape, the fields fem.border and fem.usage are no longer necessary.

The additional fields cporder, gporder, weak, dweak, constr, and expr are available in the fields fem.equ 286, fem.bnd 288, fem.edg 290, and fem.pnt 292. A user can define new field variables in terms of others in the fields fem.expr 284, fem.equ.expr, fem.bnd.expr, fem.edg.expr, and fem.pnt.expr. This may provide an advantage if included in an embodiment, for example, in which an equation may include the same expression several times.

In the field fem.expr 284 a user can put variable definitions that apply on all domain groups (of all dimensions). The field fem.expr 284 is a cell vector of alternating variable names and expressions. In fem.equ.expr a user can put variable definitions that are in force on subdomains. For example, fem.equ.expr={‘W’ ‘B*H/2’ ‘div’ ‘ux+vy’}; defines W=B*H/2, and div=ux+vy on all subdomain groups. The defining expressions in the fem.equ.expr cell vector can be cell vectors, for instance fem.equ.expr={‘v’ {‘a+b’ ‘a−b’} ‘w’ ‘pi*x*b’}. This defines v to be a+b on subdomain group 1, and a−b on subdomain group 2. The use of an empty vector [ ] instead of an expression means that the variable is not defined on the corresponding subdomain group. For example, fem.equ.expr={‘v’ {‘a+b’[ ]}}; means that v=a+b on subdomain group 1, and v is undefined on subdomain group 2. Similarly, variable definitions on boundaries, edges, and vertices are put in fem.bnd.expr, fem.edg.expr, and fem.pnt.expr, respectively.

The integrals occurring in the assembly of the matrices are computed numerically using a quadrature formula. The order of this quadrature formula is specified in the fields fem.equ.gporder, fem.bnd.gporder, fem.edg.gporder, and fem.pnt.gporder. The fem.***.gporder fields are entered in the dialog box of FIG. 38 for subdomains. There are similar dialog boxes for boundaries, edges and points. The field fem.equ.gporder gives the order for integrals over subdomains. Fem.equ.gporder can be a number or a cell vector. In the first case, fem.equ.gporder applies to all subdomain groups. In the second case, fem.equ.gporder{i} applies to the ith subdomain group. Fem.equ.gporder{i} can be a number or a cell vector of numbers. In the latter case, fem.equ.gporder{i} {k} applies to the kth equation in coefficient or general form, and the kth integrand fem.equ.weak{i} {k} in the weak formulation.

Similarly, fem.bnd.gporder, fem.edg.gporder, and fem.pnt.gporder gives the order for integrals over boundaries, edges, and vertices, respectively. The default value of the gporder fields is twice the maximum order of the shape functions being used.

The pointwise constraints are enforced in the Lagrange points of a certain order. This order is given in the fields fem.equ.cporder, fem.bnd.cporder, fem.edg.cporder, and fem.pnt.cporder. These fields have the same syntax as the gporder fields. The field fem.equ.cporder gives the order for constraints on subdomains. Fem.equ.cporder can be a number or a cell vector. In the first case, fem.equ.cporder applies to all subdomain groups. In the second case, fem.equ.cporder{i} applies to the ith subdomain group. Fem.equ.cporder{i} can be a number or a cell vector of numbers. In the latter case, fem.equ.cporder{i} {k} applies to the kth constraint on subdomain group i. Similarly, fem.bnd.cporder, fem.edg.cporder, and fem.pnt.cporder gives the order for constraints on boundaries, edges, and vertices, respectively. The default value of the cporder fields is equal to the maximum of the orders of the shape functions being used. The fem.***.cporder fields are entered in the dialog box of FIG. 38 for subdomains. There are similar dialog boxes for boundaries, edges and points.

Equations may be represented in weak form are stored in the fields fem.equ.weak, fem.bnd.weak, fem.edg.weak, and fem.pnt.weak. In one embodiment, the field fem.equ.weak contains the integrand in the integral over subdomains. Fem.equ.weak can be a string expression or a cell vector. In the first case the expression applies to all subdomain groups. In the second case, fem.equ.weak{k} applies to the kth subdomain group. Fem.equ.weak{k} can be an expression or a cell vector of expressions. In the latter case, the expressions in the cell vector are added. In the expressions representing the integrand, the test function corresponding to a variable v is denoted v_test. Then v_test will have the same shape functions as v. Similarly, the fields fem.bnd.weak, fem.edg.weak, and fem.pnt.weak contain integrands that are integrated over boundaries, edges, and points, respectively. All these integrals may be included on the right-hand side of the weak equation.

It should be noted that the function v_test as used herein is described in finite element literature, for example, as in Claes Johnsson, “Numerical Solution of Partial Differential Equations by the Finite Element Method”, Studentlitteratur, ISBN 91-44-25241-2, Lund, Sweden, 1987.

For a time-dependent problem, the terms containing time derivatives may be stored in fem.equ.dweak, fem.bnd.dweak, fem.edg.dweak, and fem.pnt.dweak. These have the same syntax as the weak fields, except that the time derivatives must enter linearly. The time derivative of a variable v is denoted v_time. The integrals defined by the dweak fields are put on the left-hand side of the weak equation. The FIGS. 39, 37, 44, and 43 shows the dialog boxes for entering the fields weak and dweak for subdomains, boundaries, edges, and points, respectively.

Eigenvalue problems are specified like time-dependent problems. Then v_time may be interpreted as minus the eigenvalue times v.

The constraints in the weak problem formulation are stored in the fields fem.equ.constr, fem.bnd.constr, fem.edg.constr, and fem.pnt.constr. These constraints are implemented pointwise. The constraints on subdomains (R(n), where n is the space dimension) are given in the field fem.equ.constr. This field can be an expression or a cell vector. In the first case, the expression fem.equ.constr is constrained to be zero on all subdomain groups. In the second case, fem.equ.constr{k} applies to the kth subdomain group. Fem.equ.constr{k} can be an expression or a (possibly empty) cell vector of expressions. These expressions are constrained to be zero on the kth subdomain group. Similarly, constraints on boundaries, edges, and vertices are defined in fem.bnd.constr, fem.edg.constr, and fem.pnt.constr, respectively.

It should be noted as described elsewhere herein that the equations, constraints (such as the boundary conditions), and the initial conditions of the PDE problem, are stored in the fields fem.equ, fem.bnd, fem.epg and fem.pnt. The field fem.equ contains information pertaining to the subdomains, i.e., geometric domains of the same dimension as the space. For a 3-D geometry, a field fem.epg is related to the edges (curves) and for both a 2-D and 3-D geometry there can be a field fem.pnt which corresponds to vertices (points). As described elsewhere herein, equations represented within this data structure may be given in a “strong” form of PDE, or in a “weak” form as an equality of integrals. The strong form has two variants, coefficient form or general form, suitable for linear and nonlinear problems, respectively. The form of this equation is specified in fem.form as described elsewhere herein. After the PDE problem is specified, the extended mesh structure fem.xmesh can be constructed. The extended mesh includes a low-level description of the PDE problem. In one embodiment, such an extended mesh may be produced, for example, by invoking a particular function. The solution to a particular set of PDE's may be computed by invoking one of the solvers as described elsewhere herein in accordance with the particular type of PDE specified, for example, time-dependent or eigenvalue PDE's.

The solution vector or the solution matrix is stored in the subfield u of the data structure field fem.sol. Additionally, other fields within the subfield fem.sol for the solution may include fields used, for example, when there are time-dependent or eigenvalue solutions produced. In other words, the data structure, for example an instance of the data structure 250, may use different fields in accordance with the different type of PDE solution formed.

It should be noted that an embodiment can also include any one or more of a variety of different software tools for the visualization and processing of data. For example, tools may be included which provide for evaluation of a particular integral or expression for a particular set of points.

As also described elsewhere herein, there are both local and nonlocal couplings that may be included in an embodiment. Generally, variables may be evaluated locally which is to say that their value at each evaluation point may be computed using information at that particular evaluation point. It is also possible to define nonlocal coupling variables for which the value at each evaluation point is the result of a computation carried out elsewhere in the same geometry or within another geometry. These variables may then be used, for example, in the PDE coefficients or during post processing. These types of variables may be referred to as the nonlocal dependencies.

Referring to FIG. 41, shown is an example of a weak formulation 1100 or weak solution form. The first equation 1102 is the weak equation, and the others are the constraints 1104. Here W is the subdomains, B is the boundaries (including outer and internal boundaries), and P is the vertices (points) defined in the geometry. The integrands W⁽¹⁾ are scalar expressions involving the dependent variables u₁, u₂, . . . , u_(N) as well as the test functions v₁, v₂, . . . , v_(N), and their derivatives. The test functions and their derivatives enter linearly.

Referring to FIG. 42, shown is a conversion from general form to weak form. Moreover, conversion from general form to weak form is performed according to the formula 1200, as shown in FIG. 42, where there is an implicit summation over the k and i indices in each product, and n is the space dimension. Affected fields are therefore ga, f, weak, da and dweak from equ and g, weak, r and constr from bnd, with weak, dweak and constr, which are the only fields remaining. Other fields within equ and bnd, such as shape, init, etc., remain unchanged.

In addition, when converting to weak form, according to FIG. 42, fem.border can be taken into account. That is to say that if fem.border is not 1 or on, there may be borders on which boundary conditions should not be applied. In order to decide in which subdomains each dependent variable is in use, and hence decide on which boundaries and borders to apply conditions, a comparison is made between the variable names in fem.dim and the field variables defined by the shape function objects being used.

Referring to FIGS. 48-50, shown is an example of another embodiment of a flowchart of steps of one method for automatically specifying one or more systems of PDEs, which PDEs are associated with non-local coupling of variables, representing the PDEs in a single combined form, and solving a system of PDEs. Many of these steps are similar to those described in connection with, for examples, FIGS. 22 and 23 described elsewhere herein. What will now be described are a highlight of additional steps with respect to other descriptions in connection with FIGS. 22 and 23.

Referring now to FIG. 48, the flowchart 2200 at step 2202,a first geometry is selected. At step 2204, a determination is made as to whether all geometries are processed. If not, control proceeds to step 2100. If all geometries are processed, control proceeds to step 2120. Generally, the processing steps set forth in FIG. 49, flowchart 2000 may be performed for each geometry of interest and are similar to other processing steps described elsewhere herein in connection with other FIGS. However, the processing steps of FIG. 49 utilize PDEs in the weak form. Thus, step 2114 provides for forming the weak form of the equations from the general form of step 2112.

Referring now to FIG. 51, shown is a flowchart of steps that may be included in one embodiment in forming and solving for a solution of PDE's. The flowchart 2124 begins with step 2500 where the weak form of PDE's are formed. At step 2502, a stiffness matrix is determined. At step 2504, a residual matrix is determined. At step 2506, a constraint matrix is determined. At step 2508, a constraint residual is determined. At step 2510, the discretized system of PDE's may be solved in accordance with the type of the system of PDE included. Depending on the type of PDE's being solved, different outputs of the various processing steps 2502-2508 may be used. This is described in more detail elsewhere herein.

Referring now to FIG. 52, shown is a flowchart of steps of one embodiment for computing a stiffness matrix. At step 2550, a loop counter variable i is initialized to 0. At step 2552, a determination is made as to whether all weak terms have been processed. If a determination is made that all weak terms have been processed, control proceeds to step 2556 where the stiffness matrix is formed by adding together all the stiffness matrices for the weak terms.

If a determination is made at step 2552 that all weak terms have not been processed, control proceeds to step 2554 where the current weak term is assigned to be the next weak term and the variable sum is initialized to 0. At step 2558, a determination is made as to whether all evaluation points have been processed. If not, control proceeds to step 2560 where P is assigned the next set of one or more evaluation points.

The total set of evaluation points may be determined using the quadrature formula. The number of points in one set of evaluation points may be chosen to optimize performance that may vary in accordance with each embodiment. For example, in an interpreted environment, such as MATLAB, the parsing of an expression can have a high computational cost. One might therefore choose a high number of points. On the other hand, processing many points “in parallel” costs lots of memory, so the number of points may also be limited in accordance with the amount of available memory.

At step 2562, Jacob_V is assigned to be the computed Jacobian of variable V at the points included in P. It is at step 2562 at which a recursive nature of this technique may be observed such that the appropriate routine is called to compute the Jacobian in accordance with the type of Variable V. Control proceeds to step 2564 where the variable Jacob_W is assigned the computed Jacobian of the variable W at the points included in P. As with step 2562, processing of step 2564 is also recursive in this embodiment of the processing steps included in flowchart 2502. Control proceeds to step 2566 where the variable sum is updated to include the product of the Jacobian of V and W multiplied by the weights of the points in P. Weights may be determined using techniques known to those of ordinary skill in the art, for example, using the quadrature formula as described in, for example, the Finite Element Method volume 1, by Zienkiewicz et al. described elsewhere herein.

Control proceeds to the determination at step 2558 where a further determination is made as to whether all evaluation points have been processed. If so, control proceeds to step 2568 where the variables weak_term_stiffness_matrix[i] and i are updated. Control proceeds to step 2552 to determine whether all weak terms have been processed.

Referring now to FIG. 53, shown is a flowchart of one embodiment for computing a residual vector. The steps in flowchart 2504 are more detailed processing steps with reference to step 2504 of flowchart 2124. At step 2600, a variable i is initialized to 0. At step 2602, a determination is made as to whether all weak terms have been processed. If so, control proceeds to step 2616 where the residual vector is formed by adding all residual vectors for the weak terms. If all weak term processing is not complete, control proceeds to step 2604 where sum is initialized to 0 and the current weak term is assigned the next weak term to be processed. Control proceeds to step 2606 where a determination is made as to whether all evaluation points have been processed. If not, control proceeds to step 2608 where P is assigned the next set of one or more evaluation points. At step 2610, the Jacobian of variable V is computed at all points in P. At step 2612, values of variable W are computed for the points in P. Steps 2610 and 2612 include recursive processing in order to determine the Jacobian and value, respectively, in accordance with variable type. At step 2614, sum is updated by the product Jacobian of V * Value of W * weight of the points P. The points P and weight may be determined using techniques described elsewhere herein. Control proceeds to step 2606 where a determination is made if all evaluation points have been processed. If so, control proceeds to step 2618 where the following variables are updated: weak_term_residual_vector[i] to store the results from the current weak term, and i.

Referring now to FIG. 54, shown is a flowchart 2506 of more detailed processing steps for determining a constraint matrix that may be included in an embodiment. At step 2650, the matrix C is initialized. At step 2652, a determination is made as to whether all constraint variables have been processed. If so, processing stops. Otherwise, control proceeds to step 2654 where W is assigned the next constraint variable. At step 2656, a determination is made as to whether all evaluation points have been processed. If so, control proceeds to step 2652. Otherwise, control proceeds to step 2658 where P is assigned the next set of one or more evaluation points. The evaluation points may be determined in accordance with values specified in the cporder field of the xfem data structure described elsewhere herein. At step 2660, the Jacobian of W is computed at the points P and the vector of partial derivatives comprising the computed Jacobian are appended as the last rows in the matrix C at step 2662. Control proceeds to step 2656.

Referring now to FIG. 55A, shown is a flowchart of steps of an embodiment that may be used in determining a constraint residual vector. At step 2680, M is initialized as the empty vector. At step 2682, a determination is made as to whether all constraint variables have been processed. If so, processing stops. Otherwise, control proceeds to step 2684 where W is assigned the next constraint variable. Control then proceeds to step 2686 where a determination is made as to whether all evaluation points have been processed. If so, control proceeds to step 2682. Otherwise, control proceeds to step 2670 where P is assigned the next set of evaluation points. At step 2672, values of variable W are computed at the points P and assigned to Val_W. At step 2674, Val_W is appended as the last rows in the vector M. Control proceeds to step 2686.

Referring now to FIG. 55B, shown is a flowchart of steps of an embodiment that may be used in determining the value of a variable at a set of points P. At step 2702, a determination is made as to whether the variable V is a basic variable. If so, control proceeds to step 2712 where the values of the basic variable V at points P are determined. Otherwise, control proceeds to step 2704 where a determination is made as to whether the variable V is of the auxiliary type. If so, control proceeds to step 2714 where values for the auxiliary variable are determined. Otherwise, control proceeds to step 2706 where a determination is made as to whether the variable V is a glued variable. If so, control proceeds to step 2716 where the value of glued variable V is determined. Otherwise, control proceeds to step 2708 where a determination is made as to whether the variable V is a mapped variable. If so, control proceeds to step 2718 for computing the value of the mapped variable V. Otherwise, the variable is an integrated type variable and its value is accordingly determined.

Referring now to FIG. 55C, shown is a flowchart of steps of an embodiment that may be used in determining the values of a basic variable at a set of points P. At step 2720, the values for a set of points are determined and returned. A vector of values is returned in which a jth element of the vector corresponds to a sum for a single point pj.

Referring now to FIG. 55D, shown in is a flowchart of steps of an embodiment that may be used in determining the values of an auxiliary variable at a set of points P. At step 2732, it is determined which variables occur in the defining expression for the auxiliary variable. Additionally, the variable i is initialized to 0. At step 2734, a determination is made as to whether all variables have been processed. If not, control proceeds to step 2736 where V is assigned the next variable and i is updated. At step 2738, the values of the variable V are determined at points P. VAL[i] is a vector of values where the jth component of VAL[i] corresponds to the jth point in P. Control proceeds to step 2734 where a determination is made as to whether all variable processing is complete. If so, control proceeds to step 2740 where the defining expression of the auxiliary variable is evaluated using VAL[i], for all entries in VAL. It should be noted that an expression may be evaluated, for example, using procedures available for use with the commercially available product MATLAB that parse the expression and apply appropriate mathematical functions to the operands. Control proceeds to step 2742 where the expression value is returned as a vector of values.

Referring now to FIG. 55E, shown is a flowchart of steps of an embodiment that may be used in determining the values of a glued variable at a set of points P. At step 2752, a determination is made as to which variables comprise the glued variable. Additionally k and VAL are initialized. Control proceeds to step 2754 where a determination is made as to whether all variable processing is complete. If so, control proceeds to step 2760 where the vector VAL is returned that includes an element for each evaluation point. Otherwise, control proceeds to step 2756 where k and V are updated. I is determined as the indices of points pj included in P that are within the domain k. Note that k indexes both the domains and the corresponding variables. At step 2758, VAL[j] is assigned the computed values of variable V at points pj included in I. In other words, the values of V are computed for those points pj for which j belongs to I. In this example at step 2758, this is performed by a call to compute_values_of var. The returned values are then placed in the appropriate indices j of the vector VAL. Control proceeds to step 2754.

Referring now to FIG. 55F, shown in is a flowchart of steps of an embodiment that may be used in determining the values of a mapped variable at points in a set P. At step 2782, global coordinates of the points in P are determined. At step 2784, the global coordinates of the mapped points are determined. At step 2786, using a search technique, the local coordinates for points Q are determined. At step 2788, V is the variable that is mapped and the values of the variable V are determined at points in Q.

Referring now to FIG. 55G, shown is a flowchart of steps of one embodiment for determining the values of an integrated variable at a set of points P. At step 2802, the evaluation points q(1) and the corresponding weights are determined as described elsewhere herein. The index vector J is also determined as described elsewhere herein. At step 2804, R is assigned the computed values of variable V at points q(l), l=1, 2, . . . . At step 2806, VAL[j] is determined. R is a vector including values of V at all points q(l), l=1, 2, . . . . A single entry VAL[j] corresponds to the value of the integrated variable at the jth point. At step 2808, VAL is returned as the vector of values.

Referring now to FIG. 55H, shown is a flowchart of steps of an embodiment for computing the Jacobian of a variable V at a set of points P. At step 2822 a determination is made as to whether V is a basic variable. If so, the Jacobian of the basic variable is determined at step 2832. Otherwise, control proceeds to step 2824 where a determination is made as to whether V is an auxiliary variable. If so, control proceeds to step 2834 where the Jacobian of the auxiliary variable V is determined. Otherwise, control proceeds to step 2826 where a determination is made as to whether V is a glued variable. If so, control proceeds to step 2836 where the Jacobian of the glued variable V is determined. Otherwise control proceeds to step 2828 where a determination is made as to whether V is a mapped variable. If so, control proceeds to step 2838 where the Jacobian of the mapped variable V is determined. Otherwise, the variable is an integrated variable and the Jacobian of the integrated variable V is determined at step 2830.

Referring now to FIG. 55I, shown is a flowchart of steps of an embodiment for computing the Jacobian of a basic variable V at points P. At step 2852, J1.DOF is determined. At step 2854, J1.VAL is determined. At step 2856, J1.EP is determined. At step 2862, the J1 is returned.

It should be noted that as described herein, for all the functions that compute the Jacobian, what is returned is not the Jacobian matrix in this embodiment. Rather, a representation of the Jacobian is returned. This representation is a list of so-called “contributions”, according to the data format for the Jacobian as described elsewhere herein.

Referring now to FIG. 55J, shown is a flowchart of steps of an embodiment for computing the Jacobian of an auxiliary variable. At step 2882, k is initialized to 0 and it is determined which variables occur in the defining expression E of the auxiliary variable. Control proceeds to step 2884 where a determination is made as to whether all variables have been processed. If not, control proceeds to step 2886 where V is assigned the next variable to be processed and k is updated. At step 2888, J[k] is assigned the computed Jacobian of the variable V at points in P. At step 2890, the partial derivative of the expression with respect to V is determined symbolically and then evaluated at points included in P. An embodiment may utilize the compute_values_of_var routine as described in connection with FIG. 55B in evaluating the expression of the partial derivative noted as DEDV in step 2890 in accordance with variable types. Other routines, compute_values_of XXX_var, are called recursively in accordance with variable type. K[k] is determined from J[k] and C[k] as described elsewhere herein. Control proceeds to step 2884 where a determination is made as to whether all variables have been processed. If so, control proceeds to step 2892 where the concatenation of K[k] for all k is performed and returned as the Jacobian.

Referring now to FIG. 55K, shown is a flowchart of steps of an embodiment for computing the Jacobian of a glued variable at a set of points P. At step 2902, it is determined which variables comprise the glued variable. Additionally, k is initialized to be 0. At step 2904, a determination is made as to whether all variables have been processed. If not, control proceeds to step 2904 where k and V are updated. Additionally, I is assigned all indices j of the points pj in P that are in the domain k. At step 2908, J[k] is determined as the computed Jacobian of V at points pj for all j in the set I. Additionally, K[k] is created from J[k] and I. Control proceeds to step 2904 where a determination is made as to whether all variable processing is done. If so, control proceeds to step 2910 where all of K[m] for all m are concatenated and returned.

Referring now to FIG. 55L, shown is a flowchart of steps of an embodiment for determining a Jacobian of a mapped variable at a set of points P. At step 2922, the global coordinates for P are determined. At step 2924, the global coordinates of the mapped points are determined. At step 2926, using a search technique, the local coordinates of the mapped points Q are determined. At step 2928, the Jacobian for V is determined at points Q where V is the variable that is mapped.

Referring now to FIG. 55M, shown is a flowchart of steps of an embodiment for determining the Jacobian of an integrated variable at a set of points P. At step 2952, evaluation points q(1) are determined and corresponding weights. Index vector J is determined. Determination of evaluation points, weights and index vector J is described elsewhere herein in more detail. At step 2954, the Jacobian of V is determined for points q(l), l=1, 2, . . . . At step 2956, K[k] is determined from J[k] and w, as also described in more detail elsewhere herein. At step 2958, K is returned.

Referring now to FIG. 56, shown is an example of an embodiment of a data structure that may be used in representing a plurality of geometries that are coupled.

The data structure 3000 is headed by a pointer xfem. Included in the data structure 3000 is an extended mesh or xmesh structure 3002. For each of the geometries, a fern data structure instance such as 3004 a-3004 n is included. It should be noted that each instance of the fern data structure such as 3004 a may be an instance of the data structure 1000 described in connection with FIG. 40. The field 3006 may include one or more elements that are used to define the different types of variables in non-local couplings. It should be noted that an embodiment may also include non-local couplings which are not between geometries but specified within a single geometry also within a single fern structure. Also shown in the data structure 3000 is the sol or solution field 3016. The sol field is a structure with a subfield u, which is a solution vector or a solution matrix. Each column in the solution matrix or vector contains the values of all the degrees of freedom. If u is solution matrix, then each column corresponds to the solution at a certain time value or eigenvalue. For time-dependent or eigenvalue problems, sol can have additional subfields containing the time values or eigenvalues. It should be noted that an embodiment may also include other fields in the data structure of FIG. 56.

Referring now to FIG. 57, shown is an instance of a non-local variable or coupling specified such as 3006 a. It should be noted that each instance of a non-local coupling included in the field 3006 may have a similar structure to that of FIG. 57. A particular instance of elemcp1 for a non-local coupling variable may include an elem field which is elcplscalar, elcplextr, or elcplproj, indentifying either a scalar coupling, an extrusion coupling, or a projection coupling, respectively, as described elsewhere herein. Other embodiments may also include other types of couplings. Also included is an src (source) field 3022 and its subfields as well as a dst (destination) field 3026. It should be noted that other data fields shown in connection with FIG. 57, such as meshp and ep, are described elsewhere herein in more detail.

It should be noted that various fields of the data structure 3006 a may be used in accordance with the different types specified in field 3020. In other words, for a scalar coupling type, different fields of the data structure may be used in contrast to when the type specified in field 3020 is one corresponding to a projection coupling. Uses of different fields included in the data structure 3006 a, for example, are described in more detail elsewhere herein in accordance with each of the different of the different types of non-local couplings and variables.

In one embodiment, the extended mesh data structure, referred to as xfem.xmesh herein, may be created by invoking a function meshextend which creates the xmesh data structure in accordance with the PDE problem as described in the xfem structure. In one embodiment, the routine meshextend may be invoked after an instance of fern structure is defined for each geometry, and may perform the following:

1. The PDE problem specification is translated to an intermediate form, which is stored as a cell vector xmesh.el. Each entry in this cell vector is an object, called an element object. An element object defines a part of the PDE problem, like variables, equations, or constraints. An element object also has a number of methods that can perform various tasks.

2. The element objects xmesh.el{i} may introduce a number of new node points within the mesh elements, in addition to the mesh vertices contained in the basic meshes xfem.fem{g}.mesh. The function meshextend organizes all these node points in the data structures in xmesh.

3. Each element object xmesh.el{i} introduces a partition of (a subset of) the domains of dimension edim. Meshextend finds the common refinement of these partitions, the mesh domain groups. This means that a mesh domain group is a maximal collection of domains that belong to the same group, for all of the partitions given by the element objects.

4. The element objects xmesh.el{i} can introduce degree of freedom names. Meshextend collects all these names in the cell vector xmesh.name. Meshextend also collects all local degrees of freedom created by the element objects into a list of global degrees of freedom. Each global degree of freedom is given a number. A degree of freedom is a pair consisting of a degree of freedom name and a node point. When the node point is specified by giving its location relative to a mesh element (that is, in local coordinates), the degree of freedom may be referred to as a local degree of freedom. When the node point is specified in global coordinates, it may be referred to as a global degree of freedom. Note that two local degrees of freedom for adjacent mesh elements can correspond to the same global degree of freedom.

5. The element objects can introduce variables that can be computed. Meshextend collects this information into a table that tells which element object computes which variable.

What will now be described is a more detailed description of the xfem.xmesh data structure follows. xmesh is a structure with the following fields:

Field name Description el Cell vector of element objects, which describe different aspects of the PDE problem. p Node points for the extended mesh in all geometries. p is a cell vector of matrices. p{g} is a matrix whose columns are the global coordinates for all node points in geometry number g. elmesh Mesh data relating to the individual element structures xmesh.el{i}. The field elmesh is a nested cell vector of so-called “element mesh structures”. More precisely, elmesh{i} {edim+1} is a structure containing mesh data related to mesh elements of dimension edim and the element object xmesh.el {i} described below. dmesh Domain mesh data, that is, mesh data not specific to individual element structures. dmesh is a cell vector of “domain mesh structures”. In other words, dmesh{edim+1} is a structure containing mesh data related to mesh elements of dimension edim, described below. name name{g} is a cell vector containing the degree of freedom names in geometry number g. gdof Numbering of the global degrees of freedom. gdof is a cell vector of matrices. The matrix gdof{g} contains global degree of freedom numbers for node points in geometry g. That is, gdof{g}(n,iname) is the number of the global degree of freedom that corresponds to node point number n and name number iname. Here n is the second index in xmesh.p{g}, and iname is the index into xmesh.name{g}. If there is no degree of freedom associated to the pair (n,iname), we have gdof{g}(n,iname) = 0.

What will be described in following text are fields in the “domain mesh structure” xmesh.dmesh{edim+1} which in this embodiment includes the fields g, ind, n, np, ix, and elvars.

Field Name Description g cell vector with geometry numbers. g{imdomgrp} is the number of the geometry that the mesh domain group imdomgrp (in dimension edim) resides in. ind cell vector with mesh domain groups in dimension edim. That is, ind{imdomgrp) is a vector containing the numbers of the domains (of dimension edim) that belong to mesh domain group number imdomgrp. n cell vector of matrices containing node point numbers for the mesh elements. The columns of n {imdomgrp} contains the node point numbers for the mesh elements within mesh domain group number imdomgrp in dimension edim. That is, n{imdomgrp}(mp,me) is the global node point number (second index into xmesh.p{g}) for node point number mp within mesh element number me in mesh domain group imdomgrp. np cell vector containing local coordinates for node points. More precisely, np{imdomgrp} is a matrix whose columns are the local coordinates for the node points in mesh elements in mesh domain group imdomgrp in dimension edim. In other words, np{imdomgrp}(1:edim,mp) are the local coordinates for node point number mp. (This is the same for all mesh elements within the mesh domain group imdomgrp.) ix cell vector containing indices into the basic mesh xfem.fem{g}.mesh. ix {imdomgrp} is a vector with basic mesh element indices for the mesh elements within mesh domain group imdomgrp in dimension edim. ix {imdomgrp}(me) is the number for the mesh element in the basic mesh xfem.fem {g} .mesh that corresponds to mesh element me in mesh domain group imdomgrp. elvars cell vector of cell matrices, containing information about variables. elvars {imdomgrp} is cell matrix with 3 rows that contains information about which variables can be computed in mesh domain group imdomgrp in dimension edim. The first row contains variable names. The second row contains the corresponding indices i for the element objects that compute these variables. The third row contains the corresponding mesh domain group indices idomgrp specific to these element objects, see below.

Now we describe the fields of the “element mesh structure” elmesh{i} {edim+1}. This structure has the fields mind, elind, rows, and name.

Field Description mind cell vector containing the indices imdomgrp for those mesh domain groups that are subsets of any domain group of dimension edim defined by element object number i. The index into mind is denoted idomgrp. elind cell vector containing the element domain group indices corresponding to the indices idomgrp. This means that the mesh domain group with number mind(idomgrp) is a subset of the domain group with number elind(idomgrp) defined by element object number i in dimension edim. rows Defines which rows in the matrix dmesh{edim+1}.n{imdomgrp} are used by element object number i. The field rows is a matrix. For the mesh domain group mind(idomgrp), and an element node point number elp (for element object number i and dimension edim), the corresponding mesh element point number mp is given by mp = rows(elp, idomgrp). name Specifies a mapping from names for local degrees of freedom to names for global degrees of freedom. The field name is a vector. Consider a variable that occurs as local degree of freedom for element object number i in geometry g and dimension edim. Let idim be its index in the variable list defined by the element object. Let iname be its index in the global list xmesh.name{g}. Then iname = name(idim).

Following are additional screenshots that may be included in an embodiment. In particular, these screenshots may be included in an embodiment in which equations in weak form may be utilized.

Referring now to FIG. 58, shown is a screen shot 3200 that may be used in connection with defining a multiphysics model that consists of several application modes and one or more different geometries. One may start in the top left portion of the screen 3200 by specifying the space dimensions such as one, two or three dimensional and edit the names of the independent variables. Application modes may then be selected from screen portion 3202 and added to the model causing them to appear on the right hand portion of the screen 3204.

It should be noted that in connection with this FIG. and others described in following text, similarities may be seen between features described here and in previous FIGS. in connection with other screen shots.

Referring now to FIG. 59, shown is an example of different file menu options that may be included in an embodiment of the model navigator, for example, as shown in connection with screen shot 3200 of FIG. 58. In connection with the file menu 3250, various options may be included in an embodiment, for example, to start a new model, open a model file already existing, and save the currently created model. Additionally, model properties may be edited and stored in the file. An embodiment may also include an option to import model data from, for example, an application such as MATLAB or from a workspace or another file. Similarly, options may exist to export the model or portions thereof to other applications or a file. What will now be described are some options that may be used in connection with the options selection tag 3254 from the screen shot menu 3250.

Referring now to FIG. 60, shown is an example of an embodiment of an options menu 3260 that may be included in an embodiment. The options menu may include, for example, certain features related to display items such as a grid or an access display as well as adding and editing constants, variables, expressions, and the like.

What will now be described are functionalities that may be included with adding and editing coupling variables 3262.

Referring to FIGS. 45A, 45B and 45C, shown are various pages of a Coupling Variable Settings dialog box 1500, respectively showing a Variables page 1500 a, Source page 1500 b and Destination page 1500 c. In the Coupling Variable Settings dialog box 1500 a user can specify non-local coupling variables. On the Variables page 1500 a shown in FIG. 45A, a user can specify the name of the coupling variable in the Variable name edit field 1502. The type of coupling is specified in the Variable type drop-down list box 1504. A user can select scalar, extrusion or projection variables from the Variable type drop-down list box 1504. After a user has entered a new variable name, the user can click Add 1506 to add the new variable name to the list of coupling variables. The user can also click Delete 1508 to delete the highlighted variable in the list.

On the Source page 1500 b, as shown in FIG. 45B, the source of the coupling is specified, i.e. the details of the evaluation undertaken. The evaluation may take place in any geometry in one or more of the domains at one of the levels subdomain, boundary, edge, or point. The levels which may be used are partly dependent on the geometry selected in the Geometry drop-down list box 1502, and partly dependent on variable type being used, so not all levels will always be available in the Level drop-down list box 1504.

When selecting geometry and domain level, the Source page 1500 b will enter the corresponding mode. Domains are then selected either from the list box 1506 or by clicking on the domains in the GUI. For extrusion variables, the expression given in the Expression edit field 1508 will be the one which is evaluated within the selected domain(s). For scalar and projection variables, the Expression edit field 1508 is replaced by an Integrand edit field (not shown), and the Integration order edit field (not shown), which gives the order of the Gauss quadrature rule which is used for integrating the variables over the source domains for the scalar variable, along the projection curve for projection variables.

The Local mesh transformation edit fields x 1510 a, y 1510 b, and z 1510 c may only be used when defining an extrusion or projection variable. The fields 1510 a, 1510 b and 1510 c contain expressions of the space coordinates, e.g. x, y, and z, or local mesh parameters, e.g. s, s1, or s2, which are then applied to create a new source mesh for use in interpolating or setting the position and direction of lines used for evaluating line integrals. The number n of these edit fields, which are enabled, depends on the dimensionality of the domain(s) used as the source. For example, n is 2 if using boundaries in a 3-D geometry, because such boundaries are 2-D surfaces. These edit fields may correspond to the cell vector src.meshp, for example, in the data structures described herein for extrusion and projection coupling variables.

On the Destination page 1500 c, as shown in FIG. 45C, a user can define where the variable is to be made available. The destination geometry and domain are specified in the same way as the source geometry, level, and domain are specified on the Source page 1500B. For scalar variables, a user may use the “Active in this domain” checkbox in order for the specified variable to be available in the selected domain. For extrusion and projection variables, defining an Evaluation point transformation in the edit fields x 1512 a, y 1512 b, z 1512 c activates the variable in the selected domain. If n of the mesh transformation edit fields were enabled on the Source page 1500 b, there will be respectively n and n−1 evaluation point transformation edit fields enabled on the Destination page 1500 c for extrusion and projection variables. Again the mesh transformation edit fields x 1512 a, y 1512 b and z 1512 c should be expressions of the space coordinates or local mesh parameters. These edit fields may correspond, for example, to the cell vector dst.ep in the data structure for extrusion and projection coupling variables.

For extrusion variables the user can set the interpolation points within the source mesh. For projection variables the evaluation for each destination evaluation point is a line integral. The position of the line is given as follows; the first n−1 coordinates in the source mesh are specified by the evaluation point transformation(s) applied to the destination evaluation point, and the n-th coordinate is allowed to vary.

Referring now to FIG. 61, shown is an example of a dialog box 3280 that may be displayed in connection with defining expressions to be used in a model. This may be used, for example, in introducing shortenings for complicated expressions for entering-parameters used in the model. An embodiment may also use expression variables in post processing, for example, if a user wants to plot a quantity on a graph defined by different application modes in different domains, an expression variable may be defined that uses the correct expression in the different domains and may be used to plot that expression variable. Displayed in a dialog box 3280 is a variables tab 3282 and a definition tab 3284.

What will now be described is the dialog box that may be used in connection with expression variable settings for the definition tab 3284.

Referring to FIGS. 46 and 47, respectively shown are examples of a variables page 1600 a and a Definition page 1600 b of an Expression Variable Settings dialog box 1600. In the Expression Variable Settings dialog box 1600, the user can define expressions to be used in a model. The Expression Variable Settings dialog box 1600 provides a convenient way to introduce short names for complicated expressions that the user wants to use when entering parameters for the model. Another use for expression variables is in post processing, where if the user wants to plot some quantity that is defined by different application modes, which are in different domains, the user can define an expression variable that uses the correct expression in the different domains and then plot the expression variable.

On the Variables page 1600 a, as shown in FIG. 46, the user can enter the name of the variable in the Variable name field 1602 to define an expression. Expressions can be either domain-based, i.e. at subdomain/boundary/edge/point level, or geometry-based, i.e., the expression is defined everywhere on the geometry. This variable type can be specified in the Variable type drop-down list box 1604.

On the Definition page, as shown in FIG. 47, the user can specify in which geometry and in which domain the expression should be defined by respectively selecting from the Geometry drop-down list 1606 and the Level drop-down list 1608. In the Expression edit field 1610, the user can enter the expression to be defined by the specified variable. The definitions are recorded in the fields fem.expr, fem.equ.expr, fem.bnd.expr, etc. in the data structure (FIG. 40) for the appropriate geometry. Where a definition is not given in the dialog for a subdomain, the corresponding entry in fem.equ.expr will be the empty matrix, which means that it is not defined, this similarly holds true for bnd, edg, and pnt.

In connection with the assigned variable names selection of the options menu 3266, an assigned variable names dialog box may be displayed as shown in connection with FIG. 62.

Referring now to FIG. 62, shown is an example of a dialog box 3290 that may be displayed in connection with assigning variables. The assigned variables dialog box may be used to edit assigned variable names for all variables belonging to application modes in a current model. Assigned variables may be used for post processing. They may be created automatically and based on a fixed name each of them gets a unique name.

In connection with application scalar variables as included in options menu item number 3268, an application scalar variable dialog box may be displayed.

Referring now to FIG. 63, shown is an example of an embodiment of an application scalar variable dialog box 3292. In some applications, scalar variables may exist that take part in mathematical model but are independent of the geometry and material for example. The value of such application specific scalar variables may be set using this dialog box. Scalar variables may be included, for example, in predefined application modes. For example, in one embodiment, in connection with an application mode related to AC power electromagnetics, scalar variables such as omega may be used in representing angular frequency. Additionally, some of the modes in which the optional electromagnetics module and structural mechanics module may be included and may also include such scalar variables. It should be noted that an embodiment may disable this menu if no such quantities exist.

In connection with the differentiation rules option menu 3270, a differentiation rules dialog box may be displayed and used in an embodiment.

Referring now to FIG. 64, shown is an example of an embodiment of a dialog box 3294 that may be used in connection with specifying additional differentiation rules. In particular, these rules may be used to symbolically differentiate coefficients and a PDE in a general form, and to compute the Jacobian of a variable.

In connection with the draw menu 3296 as displayed, for example, in FIG. 60, different options may be available in connection with a particular dimension of the geometry of the model.

Referring now to FIG. 65, shown is an example of an embodiment of a point menu 3310. In this example, the point menu 3310 may include three options or items including point mode, point settings, and an option to view point data as point coefficients. The point mode option may be used to enter or indicate point mode. Point settings may be used to specify point settings for selected points. The “view as point coefficients” option may be used to view or edit application specific point settings as generic point settings.

Referring to FIG. 43, shown is an example of a Point Settings dialog box 1300. The Point Settings dialog box allows 1300 permits entry of fem.pnt.weak, fem.pnt.dweak and fem.pnt.constr fields on each point in the respective weak 1302, dweak 1304, and constr 1306 fields of the dialog box 1300.

Referring now to FIG. 66, shown is an example of a dialog box 3312 that may be used in connection with displaying point settings in coefficient view. When this option is turned on, point settings open a new tab dialog box, such as 3312. Using this dialog box, initial values may be specified and shape functions may also be specified on the init and elements page, respectively, in addition to the weak terms on the weak page.

Referring now to FIG. 67, shown is an example of an embodiment of a menu for edge options that may be used in connection with three dimensional models in this embodiment. The edge menu 3314 in this example contains three options. The first option is edge mode where edge mode is enable or indicated. In the edge settings option which will be explained in more detail below, edge settings may be specified for selected edges. Additionally, an option in this embodiment may be included to view application specific edge settings as generic edge settings.

Referring to FIG. 44, shown is an example of an Edge Settings dialog box 1400. The Edge Settings dialog box 1400 permits entry of fem.edg.weak, fem.edg.dweak, and fem.edg.constr fields on each edge (in 3-D) in the respective weak 1402, dweak 1404 and constr 1406 fields of the dialog box 1400. In coefficient view, there are similar user interfaces for adding weak, dweak, and constr contributions on boundary and subdomain level.

Referring now to FIG. 68, shown is an example of a dialog box 3320 that may be used in connection with edge settings. In connection with the different tabs included, initial values may be specified with the init tab. Shape functions may be specified with the elements tab. Additionally, weak terms may be specified on the weak tab.

Referring now to FIG. 69, shown are examples of boundary menu options that may be enabled in connection with different dimensional geometries. In particular, the boundary menu may appear as in 3332 in connection with one and two dimensional geometries and may appear as in 3334 for three dimensional objects or geometries.

The boundary mode option may be used to enable or indicate boundary modes. The boundary settings option may be used to specify boundary conditions for selected boundaries. Enable borders may be used to enable or disable the assembly of boundary conditions on subdomain borders. View as boundary coefficients may be used to view or edit application specific boundary conditions as generic boundary conditions. The show direction arrows option may be used to show direction arrows for the different boundaries. It should be noted that certain menu options may be enabled in accordance with the dimensions of a geometry. The option for generating coupled equation variables is used to enable or disable the automatic generation of the equation-based variables on boundaries. Similarly, the generate coupled-shaped variables may be used to enable or disable the automatic generation of shape function-based variables on boundaries.

In one embodiment, one can generate boundary-coupled variables corresponding to the basic variables and their derivatives, and call them boundary shape variables, such as for example in connection with menu option 3332 a. In an embodiment, one may also be able to generate boundary-coupled variables corresponding to the terms in an equation on coefficient or general form, and call them equation-based boundary variables, for example, as in connection with option 3332 b.

Referring now to FIG. 70, shown is an example of a dialog box 3340 that may be used in connection with boundary settings. In particular, the weak tab in 3340 is displayed which may be used to specify weak terms and constraints in connection with specifying boundary conditions.

Referring now to FIG. 71, shown is an example of a dialog box 3344 that may be used in connection with PDE models having more than one dependent variable. The dialog box shows the boundary settings for coefficient form PDE with two dependent variables. One may select boundaries from the list box, or using other techniques that may be included in an embodiment.

Referring now to FIG. 72, shown is an example of a dialog box that may be used in connection with the subdomain settings. In particular, when the weak tab is activated as shown in the dialog box 3350, weak terms may be specified on selected subdomains.

Referring now to FIG. 73, shown is an example of an embodiment of menus and dialog boxes that may be displayed in connection with a solve or solutions menu that may be used in connection with specifying options for partial differential equation solutions and solving methods. In particular, the solve menu options may be included as in 3372. In connection with the parameters option, the dialog box for solver parameters 3374 may be displayed.

Referring now to FIG. 74, the multiphysics page or tab in connection with the solver parameters option may cause dialog box 3380 to be displayed. Using this multiphysics tab, the user may control how to solve a multiphysics model which is specified. For example, this dialog box 3380 may be used to specify which variables to solve for and how initial value should be updated if you want to solve using an iterative approach where the previous solution becomes the initial values in a next iteration. In the solve for variables section, a list of all application modes may be displayed. The solver may solve all variables in all selected application modes. By default, an application mode in the model is selected. If the show variables option is checked, the list shows all of the variables in the model and you may individually select among all of the variables in the application modes. In the update mechanism for the initial value U section, it may be specified how to update the solution used as an initial value. For example, if the store solution button is active, the solution used for the initial value or valuation is updated using the current solution. In selecting the storage solution automatically option, this causes the solution used for the initial value to be stored automatically when a new solution has been computed. From the use solution number drop-down box, a user may select which solution to use. For time-dependant models, the default is to use the solution at the last output time.

Referring now to FIG. 75, shown are examples of a menu and dialog box that may be used in connection with a multiphysics menu option. The dialog box 3394 may be used to select application modes for a current multiphysics model. It should be noted that for PDE modes, an embodiment may have more than one dependent variable. The space dimension of the model may be determined by entering one or more space-separated variable names. For example, in the screen dialog box 3394, three independent variables, X, Y and Z, are entered and it is considered a 3-D geometry.

In reference to the foregoing dialog boxes, user interfaces, and the like, data may be entered for each geometry. In this embodiment, there are menu options and items used in connection with weak equations that may be stored in fields and subfields of the fern data structure, for example as shown in FIG. 40, and the xfem data structure, for example, as shown in FIG. 56. In particular, data used in connection with the weak dialog tabs may be stored in fem.***.weak, fem.***dweak, and fem.***.constr fields. Data used in connection with the “Expression Variables” dialogs as described herein may be used in adding variables, for example, to the fields fem.expr and fem.***.expr in data structures described herein.

An embodiment may associate particular functionality described herein with particular functions or methods. In one embodiment, each of the following is associated with a particular, method: computing the values of a variable, computing the Jacobian of a variable, assembling the residual vector of a weak term, assembling the stiffness matrix, assembling the constraint residual vector, and assembling the constraint Jacobian.

It should be noted that as described elsewhere herein, an embodiment may include functions, routines or methods in accordance with each particular implementation that embody functionality described herein. For example, in one embodiment, an object oriented scheme may be used in which, geometry objects may be predefined in a class structure as, may be included in an embodiment using a C++ programming language for example. Additionally, as also described elsewhere herein, different methods may be invoked in accordance with each particular class.

Several specific examples, as set forth herein, include a scalar coupling example, an extrusion coupling example, and a projection coupling example, followed by a discussion of the Weak solution form and the Solvers; Sparsity of Jacobian and Non-Local Dirichlet Boundary Conditions. In addition, other specific examples, as set forth herein, include a Packed Bed Reactor example and a Magnetic Brake example.

Extended Multiphysics Coupling Variables

Variables in FEMLAB are generally evaluated locally—their value at each evaluation point is computed using information only from that evaluation point. In contrast, the value of a coupling variable is the result of a computation carried out elsewhere in the geometry or even in another geometry altogether. When used in the PDE and boundary conditions, the result is the introduction of non-local dependencies—extended multiphysics—as opposed to ordinary multiphysics, which refers to dependencies between variables in same geometric location.

The coupling variables are extremely powerful in their ability to make the values of an expression available non-locally. The coupling variables are not only useful for modeling coupled problems—they can also be used solely for post processing and visualization purposes.

All coupling variables are defined in two steps. First define the source, i.e., the domains in which the evaluation takes place, the nature of that evaluation, and the name given to the resulting variable; secondly define the destination, i.e. the domains within which it is possible to use the resulting variable.

There are three kinds of coupling variables implemented: scalar, extrusion, and projection.

Specifying Non-Local Couplings

In the graphical user interface you can define coupling variables by using the Coupling Variable Settings dialog box from the Options menu as shown in FIG. 76.

The Source and Destination tabs allow you to define the source and destination details and the Variable type gives the choice of scalar, extrusion, or projection variables.

Scalar Couplings

Use scalar coupling variables to make scalar values available elsewhere in your model. The source of the scalar value can be an expression in a vertex. In addition, the source of the scalar value can be the integral of an expression over one or several subdomains, boundaries, or edges. The destination of the scalar variable can be the full geometry, one or several subdomains, boundaries, edges, or vertices.

Scalar Coupling Example

As a simple example, consider the case of Poisson's equation on a single rectangular domain as shown in FIG. 77. The integral of the square of the solution is used as in-flux in a Neumann boundary condition on the right boundary. There is a Dirichlet boundary condition on the left boundary, and the top and button boundaries have zero in-flux. The problem is nonlinear so you have to use the nonlinear solver. The right boundary condition contains the scalar coupling variable in a coefficient, so the weak solution form must be used.

$\begin{matrix} {{\Delta \; u} = 1} & {{on}\mspace{14mu} \Omega} \\ {u = x} & {{on}\mspace{14mu} {\partial\Omega_{1}}} \\ {\frac{\partial u}{\partial n} - 0} & {{on}\mspace{14mu} {\partial\Omega_{2.3}}} \\ {\frac{\partial u}{\partial n} = {- {\int_{\Omega}{u^{2}{\Omega}}}}} & {{on}\mspace{14mu} {\partial\Omega_{4}}} \end{matrix}$

Model Navigator

Start FEMLAB and select the 2-D, Coefficient, Nonlinear, PDE mode in the Model navigator. Use the Lagrange-Quadratic element type. Press the More button, and select solution form Weak.

Draw Mode

-   -   Draw a single rectangle of any size.

Boundary Mode

-   -   Change the following boundary coefficients:

BOUNDARY 1 2-3 4 Type Dirichlet Neumann Neumann r x g 0 int2

Subdomain Mode

-   -   Use the default PDE coefficients (Poisson's equation).     -   Open the Add/Edit Coupling Variables dialog box.     -   Enter the variable name int2, and choose the default type         Scalar. Press Add.     -   Go to the Source page and select subdomain 1. Enter −û2 in the         Expression field, and enter 4 in the Integration order field.     -   As a simple rule, the integration order can be the maximum of         the quadrature order for the integration of the shape functions         of the variables in the expression.     -   On the Destination page, select boundary 4 and check Active in         this domain.     -   Return to the Variables page to check the definition. Finally,         press OK.

Solve Problem

-   -   Press the Solve Problem button to start the simulation.

Post Mode

-   -   Open the Subdomain Integration item on the Post menu. Type −û2         in the expression field. Select subdomain 1 and press Apply. The         integral of the solution is displayed in the message log.     -   Open the Plot Parameters dialog box. Check Contour and uncheck         Surface. Press the Contour tab. Change the Contour expression to         ux. Click in the GUI on the right boundary, and verify that the         in-flux is equal to the integral.

Brief Examples of Scalar Couplings

One example of scalar couplings is to use scalar values from a vertices on the adjacent boundary as shown in FIG. 78A. In structural mechanics, you can use this type of coupling to formulate displacement constraints along a boundary in terms for the displacements of the end point.

Another example is to use the integral over a subdomain in a 2-D geometry along a subdomain in another 1-D geometry as shown in FIG. 78B. This is useful for process industry models, where two different processes interact.

Extrusion Couplings

An extrusion coupling variable takes values from the source domain(s) by interpolation of an expression at points that are dependent in some way on the position of the evaluation points in the destination domain(s).

When the destination domain has more space dimensions than the source domain, the variable performs extrusion of values. The extrusion coupling variable can also be used for mapping values from the source to the destination. This is applicable when the source and destination domains have the same number of space dimensions.

The method employed is that first a one-to-one transformation is applied to the mesh of the source domain(s). This transformation may be trivial and leave the coordinates unchanged, but it can also be used to rescale, stretch, bend, or reflect the mesh. Then a second transformation is applied to the evaluation points in the destination domain(s), and the resulting points are used for the interpolation of an expression at points in the transformed source mesh.

Extrusion Coupling Example

Consider the case of a single rectangular domain, where the source term in Poisson's equation comes from the inward flux over the right boundary for the corresponding y coordinate.

$\begin{matrix} {{\Delta \; u} = {\frac{\partial}{\partial n}{u\left( {x_{2},y} \right)}}} & {{on}\mspace{14mu} \Omega} \\ {u = {xy}} & {{on}\mspace{14mu} {\partial\Omega}} \end{matrix}$

The FIG. shown in FIG. 79 illustrates the extrusion process. The values of the in-flux on the boundary become available throughout the domain by extrusion along the y-axis. The source transformation mapping is y, and the destination transformation mapping is y.

The problem is linear so you can use the linear solver. We use the weak term to specify the source term in the Poisson equation, so we do not have to use the weak solution form.

Model Navigator

-   -   Start FEMLAB and select the 2-D, Coefficient, Linear, PDE mode         in the Model navigator. Use the Lagrange-Quadratic element type.

Draw Mode

-   -   Draw a single rectangle of any size.

Boundary Mode

-   -   In boundary mode, select all boundaries. Set the r coefficient         to x*y.

Subdomain Mode

-   -   On the Weak tab, set the subdomain 1 weak term to u_test*flux.         (Poisson's equation with source flux).     -   Open the Add/Edit Coupling Variables dialog box.     -   Enter the variable name flux and choose the default type         Extrusion and press Add.     -   Go to the Source page and select boundary 4. Enter ncu in the         Expression field, and set local mesh transformation to y.     -   On the Destination page, select subdomain 1, and set local mesh         transformation to y.     -   Return to the Variables page to check the definition. Finally,         press OK.

Solve Problem

-   -   Press the Solve Problem button.

Post Mode

-   -   On the Surface tab, change Surface expression to flux.     -   On the Line tab, check Line plot, and select ncu as Line         expression.     -   Press OK.

The plot shows both the value of the flux variable on the destination domain and the source ncu on the boundary.

Brief Examples of Extrusion Couplings

One application of extrusion couplings is to mirror the solution in the x-axis as shown in FIG. 80A. This can be very useful for post processing. The source transformation mapping is x, y, and the destination transformation mapping is x, −y.

Another example is to extrude the solution in the 1-D geometry to the 2-D along the s axis as shown in FIG. 80B. The source transformation mapping is x, and the destination transformation mapping is r.

Yet another example is to map values on the lower boundary to the right boundary on the same rectangle as shown in FIG. 80C. The source transformation mapping is (x+1)/2 and the destination transformation mapping is y.

Projection Couplings

A projection coupling variable takes values from the source domain(s) by evaluating a series of line integrals within the source domain(s), where the line positions are dependent on the positions of the evaluation points in the destination domain(s). In this way you can evaluate the average of a variable over one space variable at a range of different points along the other space axis, giving a result which varies over the latter space variable.

The method employed is that first a one-to-one transformation is applied to the mesh of the source domain(s). The last space dimension in the transformed mesh is the one integrated over, so the lines used to integrate are vertical in the transformed source mesh. The placement of the vertical lines in the transformed source mesh is given by the positions of the transformed destination evaluation points. The integrals are then carried out in the source domain(s) over lines which correspond to the vertical lines in the transformed source mesh.

Then a second transformation is applied to the evaluation points in the destination domain(s), and the resulting points are used for the interpolation of an expression at points in the transformed source mesh.

Brief Examples of Projection Couplings

Referring to FIGS. 81A-81C, for each point r return

${v(r)} = {\int_{\underset{{({x,y})} \in S_{2}}{y = {r/2}}}{{u\left( {x,y} \right)}{x}}}$

The source transformation mapping is y, x, and the destination transformation mapping is r/2.

For each point (0,s) return

${v\left( {0,s} \right)} = {\int_{\underset{{({x,y})} \in S_{2}}{y = s}}{{u\left( {x,y} \right)}{x}}}$

The source transformation mapping is y, x, and the destination transformation mapping is s.

For each point (r,0) return

${v\left( {r,0} \right)} = {\int_{\underset{{({x,y})} \in S_{2}}{y = {r/2}}}{{u\left( {x,y} \right)}{x}}}$

The source transformation mapping is y, x, and the destination transformation mapping is r/2.

Also non-rectangular domains can be swept by the integration. Only the source domains will be included in the integrals. Other domains and the external area will be excluded from the integrals.

The Weak Solution Form and the Solvers

FEMLAB computes the exact Jacobian contribution for the coupling variables when the coupling variables are evaluated as weak terms. The easiest way of achieving this is by using solution form Weak. It can also be achieved by with solution form Coefficient or General by specifying all coupling variables in weak terms on the Weak tabs.

If you use a coupling variable in a coefficient, without using solution form Weak, the Jacobian is likely to be incorrect—and the nonlinear solver might not converge even for linear couplings.

For stationary problems with coupling variables, you should always use the nonlinear solver—it can sometimes be difficult to see if the problem is nonlinear or not. If you are sure about the linearity of the problem, and coupling variables only occur in weak terms, the linear solver can be safely used.

Sparsity of Jacobian

The Jacobian for problems formulated using the finite element method is usually large, but rather sparse, i.e., with relatively few nonzero elements. This is because the solution at each node in the mesh can be dependent at most on the degrees of freedom from the neighboring mesh elements. If however coupling variables are introduced, non-local dependencies are introduced, filling up the rows and columns of the affected source and destination nodes. This extra filling may make the Jacobian matrix slightly less sparse (in which case the solution speed is only slightly affected) or it may make it a great deal less sparse (in which case the memory use and CPU time involved in solving the problem may be increased a great deal). For this reason care should be taken when introducing non-local couplings.

Non-Local Dirichlet Boundary Conditions

When using coupling variables in Dirichlet boundary conditions, the constraint is handled by adjusting both the source and the destination values until the constraint is satisfied. This corresponds approximately to how periodic boundary constraints are handled in FEMLAB, and this may be appropriate in the context of the problem being modeled. Often, however, it is more appropriate to leave the source unaffected and constrain only the destination.

Multidisciplinary Models Magnetic Brake

This example studies a magnetic brake that slows down a copper disk rotating in the magnet's air gap as illustrated in FIG. 86. The rotation induces currents, and forces along the current lines impede the disk's motion.

This time-dependent problem will be solved in two different ways: first using FEMLAB's extended multiphysics feature, and second as a Simulink simulation. In both cases the stationary problem of computing the magnetic field in the disk given a certain angular velocity ω will be solved first.

Assume the disk rotates around the z-axis with angular velocity ω. The velocity v at a point (x,y) is then

v=ω(−y,x,0).

When the disk is inserted in the air gap and it encounters the magnetic field B₀, the configuration induces a current density j according to Lorentz' equation:

$\quad\left\{ \begin{matrix} {E + {v \times {\left( {B + B_{0}} \right) \cdot \frac{1}{\sigma\sigma}}j}} \\ {{\nabla{\times E}} = 0} \\ {{\nabla{\times B}} = {\mu \; {j.}}} \end{matrix} \right.$

In these equations, B represents the magnetic field, E the electric field, μ the permeability, σ the electric conductivity, and d the plate's thickness. This example uses the Dirichlet boundary condition B=0.

In this model the magnetic flux B has only a vertical component and the currents and electric field have no z-components. Solving for B gives the following scalar partial differential equation:

−div(∇B+μσdω(B+B ₀)( ))=0

where B is the z-component of B and B₀ equals the z-component of B₀.

Now consider how the system evolves over time. The disc is slowed down by the induced torque and an ordinary differential equation (ODE) must be set up to model the angular velocity ω.

To obtain the time derivative of the angular velocity ω, the torque arising from the induced currents must be computed. For a small surface element, the force equals

dF=j×(B+B ₀)dxdy

and integrating over the disk gives the total torque:

$M = {\int_{Disk}{\frac{1}{\mu}r \times \left\{ {\left( {\nabla{\times B}} \right) \times \left( {B + B_{D}} \right)} \right\} {x}{{y}.}}}$

In this case, M has only a z-component with the value

$M = {\int_{Disk}{\frac{1}{\mu}{\left( {{y\frac{\partial B}{\partial x}} - {x\frac{\partial B}{\partial y}}} \right) \cdot \left( {B + B_{0}} \right)}{x}{{y}.}}}$

Thus the ODE for ω may be formulated as

${J\frac{\omega}{t}} - M$

where the moment of inertia J for a disk with radius r equals

$J = {{m\frac{r^{2}}{2}} = {\frac{\rho {r^{4}}\pi}{2}.}}$

Model library FEMLAB/Multidisciplinary/magnet_brake

Using the Graphical User Interface-Fixed ω

Before solving the time-dependent problem, consider first the problem where ω is fixed.

Select the 2-D, Coefficient, Linear stationary PDE mode in the Model Navigator. Click on the button marked More, change the Dependent variable name to B and then click OK.

Options and Settings

-   -   To help when drawing the geometry, set axis and grid settings:

AXIS G

X min −0.15 X spacing 0.05 X max 0.15 Extra X 0.03 0.07 Y min −0.1 Y spacing 0.02 Y max 0.1 Extra Y

indicates data missing or illegible when filed

-   -   Enter the following constants:

NAME EXPRESSION K 4e−7 * pi {circumflex over ( )} 5.99e7 * 0.02 w 2 * pi * 100

The variable w represents the fixed angular velocity ω. The variable K is the product of μ, σ and d.

Draw Mode

-   -   Draw a circle centered at (0,0) with a radius of 0.1.     -   Draw a square centered at (0.05,0) with each side 0.04 units         long as shown in FIG. 87.

Boundary Mode

-   -   Check that the boundary settings are:

BOUNDARY 5, 6, 7, 8 Type Dirichlet h 1 r 0

Subdomain Mode

-   -   Enter PDE settings as shown:

SUBDOMAIN 1, 2 c 1 a, f, d_(a) 0 α K * w * y −K * w * x γ −K * w * BO * y K * w * BO * x

-   -   The applied field B₀ is used here and it has not been defined.         It is different in the two subdomains, so it's best to use the         Add/Edit Expressions dialog     -   Enter the name BO, select type subdomain and click Add in FIG.         88.     -   Click the Definition tab, select subdomain 1 and enter the         expression 0     -   Select subdomain 2 and enter the expression 1e-3. Then press OK         in FIG. 89.

Mesh Mode

-   -   Open the Mesh Parameters dialog box by selecting Parameters . .         . from the Mesh menu and set Max. edge size, general to 0.04.     -   Click on More and enter 20.01 in the Max element size for         subdomains box as shown in FIG. 90.     -   Press OK and then press the Initialize Mesh button.     -   Press the Refine mesh button.

Solve Problem

-   -   Press the Solve Problem button to solve the problem. (Time to         solve: 5 s) as shown in FIG. 91.

Using the Programming Language—Fixed ω

% Clear the FEM structure, set the variable name and % choose quadratic elements. clear fem fem.dim=‘B’; fem.shape=2; % Specify the constants K and w. fem.variables={‘K’,4e−7*pi*5.99e7*0.02,... ‘w’,2*pi*1001; % Create the geometry. fem.geom=circ2(0,0,0.1)+rect2(0.03,0.07,−0.02,0.02); % Specify the boundary conditions, i.e. homogeneous Dirichlet % conditions at the edge of the disk (boundary elements 5, 6, 7 % and 8). fem.bnd.h=1; fem.bnd.r=0; fem.bnd.ind={5:8}; % Specify the PDE coefficients. fem.equ.c=1; fem.equ.al={{{‘K*w*y’ ‘−K*w*x’}}}; fem.equ.ga={{{‘−K*w*B0*y’ ‘K*w*B0*x’1}}; fem.equ.expr-{‘BO’ {‘0’ ‘1e−3’}}; % Generate the mesh. fam.mesh=meshinit(fem, ‘hmax’,{0.04 [ ] [ ] [2 0.01]}); fem.mesh=meshrefine(fem); % Solve the problem and plot the solution. fem.xmesh=meshextend(fem); fem.sol=femlin(fem); postplot(fem,’tridata’, ‘B’, ‘tribar’, ‘on’,... ‘trirefine’,10, ‘axisequal’, ‘on’);

Using the Graphical User Interface—Time-Dependent ω

In this section FEMLAB's extended multiphysics feature will be used to solve the time-dependent problem.

The approach taken here will be to set up a second geometry to handle the ODE for angular velocity

${J\frac{\omega}{t}} - M$

-   -   and then use extended multiphysics element structures to allow         variables from each geometry to be made available when solving         the problem in the other geometry.

Note An alternative approach is to use only one geometry and introduce a new variable w, active at a single point within that geometry using a Point weak form, application mode. In this alternative the same coupling variables M and w are used but the source and destination domains would have to be suitably altered. The ODE for w would then be specified using the coefficients on the Weak tab in the Point settings dialog; first multiply both sides of the ODE by the test function for w, then set dweak and weak to be the left and right hand side respectively, i.e. J*w_time*w_test and m*w_test

Options

-   -   Add the following constants to the variable list which already         includes K and w:

NAME EXPRESSION J 8960 * 0.02 * 0.1

 4 * pi/2 mu 4e−7 * pi

indicates data missing or illegible when filed

-   -   Select the variable w in the list and Delete it so the list         consists only of K, J and mu. The variable w here will be         replaced by the dependent variable w from the ODE.     -   In the Add/Exit Expressions dialog box, select the variable BO         in the list and change its definition in subdomain 2 to 0.1

Add Geometry

Now add the new geometry to handle the ODE. An ODE can be thought of as a zero-dimensional PDE, so in principle a zero-dimensional geometry is all that is required here, but since there is no support for this in the graphical user interface, a trivial one-dimensional geometry will be used instead. In addition, the use of coupling variables means weak solution form must be used.

-   -   From the Multiphysics menu, choose Add/Edit Modes.     -   Change the Solver type to Time dependent and the Solution form         to Weak.     -   Click on the button marked Add to the right of the Geometry name         list.     -   Select I-D using the Dimension radio buttons.     -   From the list on the left, select PDE, coefficient form.     -   Change the Dependent variable name to w.     -   Click on the >> button in the middle of the dialog box to add         this mode and geometry to the model.     -   Change the Solution form to Weak for this new geometry as well.     -   Click OK.

Draw Mode

-   -   From the Draw menu, choose Specify geometry.     -   Enter 0 and 1 in the Start and Stop fields respectively.     -   Click OK.

Define Coupling Variables

There are two extended multiphysics couplings in this model. In other words, two variables which are to be made available beyond the domains in which they exist naturally.

Firstly, the source term M in the ODE described in geometry 2 was defined earlier to be

$M = {\int_{Disk}{\frac{1}{\mu}{\left( {{y\frac{\partial B}{\partial x}} - {x\frac{\partial B}{\partial y}}} \right) \cdot \left( {B + B_{0}} \right)}{x}{y}}}$

-   -   so the result of this integral over subdomains 1 and 2 in         geometry 1 must be made available in geometry 2 as the variable         M.

Secondly, the angular velocity variable w is used in the coefficients α and y the PDE in geometry 1. Previously w was defined in the Add/Edit Constants dialog box, but this time it must be taken from geometry 2. Thus the dependent variable w in geometry 2 must be made available in the subdomains of geometry 1.

Define M first

-   -   Open the Add/Edit Coupling Variables dialog     -   Enter the variable name M and select the default type scalar     -   Press Add in FIG. 92.     -   Click on the Source tab and then select Geom1, subdomain level         as the source     -   Select subdomains 1 and 2 and set the integration order to 2 and         the integrand (B+B0)*(y*Bx−x*By)/mu as shown in FIG. 93.     -   Click on the Destination tab and select Geom2, subdomain level     -   Select subdomain 1 and check the Active . . . box as shown in         FIG. 94.

Now make w available in geometry 1

-   -   From the Variables tab, add a scalar variable with the name w     -   On the Source tab set the source as Geom2, subdomain 1, with an         integrand w and integration order 1.     -   Set the Destination as Geom1, subdomains 1 and 2     -   Press Apply.

To check the variables have the correct source and destination domains, click on the Variables tab in FIG. 95.

Note that the definition of w here means ‘use the integral of w over subdomain 1 in geometry 2’, but since w will be constant over the whole subdomain and the subdomain has length l, this is the same as simply taking the value w at any point in the subdomain.

Boundary Mode

-   -   Set the boundary settings:

BOUNDARY 1, 3 Type Neumann q 0 g 0

Subdomain Mode

-   -   Enter PDE settings as shown:

SUBDOMAIN 1 C, ∂, α, β, γ O d_(s) J f M init 2 * pi * 200

Mesh Mode

-   -   Open the Mesh Parameters dialog box by selecting Parameters . .         . from the Mesh menu and set Max. edge size, general to 1.     -   Press OK and then press the Initialize Mesh button.     -   Select Geometry 1 from the Multiphysics menu.     -   Press the Initialize Mesh button. This resets the mesh to a         coarser mesh than the one used in the fixed ω case in order to         shorten the solution time for the time dependent case.

Solve Problem

-   -   Open the Solve parameters dialog box and turn to the         Timestepping page.     -   Set the Output times to 0 8, and select fldae as the         Timestepping algorithm, with Relative tolerance 1e-3 and         Absolute tolerance 1e-5.     -   Click OK.     -   Press the Solve Problem button on the toolbar.

Plot Mode

Once the problem has been solved, the results can be visualized in a number of ways.

-   -   An animation of the dissipation of B over time can be shown by         pressing the Animate button.     -   For a graph of the ω against time, select Geometry 2 from the         Multiphysics menu and open the Cross-section plot parameters         dialog box from the Post menu. Select all the time steps in the         list box and select Point plot. Then, on the Point sheet, make         sure that the Point expression is w and click OK as shown in         FIG. 96.     -   For a graph of dω/dt against time, follow the same procedure as         for ω, but set the Point expression to M/J instead.

Results

The plots for ω and dω/dt against time are shown in FIGS. 97A-97B.

Packed Bed Reactor

One of the most common reactors in the chemical industry, for use in heterogeneous catalytic processes, is the packed bed reactor as shown in FIG. 82. This type of reactor is used both in synthesis as well as in effluent treatment and catalytic combustion. The reactor consists in essence of a container filled with catalyst particles. These particles can be contained within a supporting structure, like tubes or channels, or they can be packed in one single compartment in the reactor.

The structure that is formed by the packed catalyst particles makes the modeling of mass and energy transport in the reactor a challenging task. The difficulty lies in the description of the porous structure, which gives transport of different orders of magnitudes within the particles and between the particles. In most cases, the structure between the particles is described as macro porous and the pore radius can be of the order of magnitude of mm. When a pressure difference is applied across the bed, convection arises in the macro pores. The pores inside the catalyst particles form the microstructure of the bed. The pore radius in these particles is often between one and ten mm.

This model presents a simple and fast alternative for studying macro- and micro-mass balances in packed beds and other heterogeneous rectors with bimodal pore distribution. The simulation gives the mass and reaction distribution, and the same type of approach for the heat balance accounts for the temperature profile in the reactor. The equations are based on simple mass balances for the macro and micro systems.

The mass balance for the macro system are based on the equation for convection-diffusion-reaction:

∇·(−D∇c+cu)+R=0

In the above equation D denotes the diffusion coefficient (m² s⁻¹), c concentration (mol m⁻³), u the velocity vector (m s⁻¹) and R denotes the reaction term (mol m⁻³ s⁻¹). The solution of the above equation requires proper boundary conditions:

c=c ₀ at ∂Ω_(inlet)

−D∇c·n=0 at ∂Ω_(outlet)

(−D∇c+cu)·n=0 at all other boundaries

At a first glance, these equations look simple to solve, especially if the velocity vector is given by an analytical expression, which is the case for plug flow in a packed bed reactor. However, the reaction term, R, depends on the transport in the micro particles, which in general is obtained by calculating the flux into the particles, at the outer surface of the particle, times the available outer surface area of the particles per unit volume:

R=A _(p) N(r−R _(p))·n

In this equation, A_(p) denotes the outer surface area of the particle per unit volume (m² m⁻³), N denotes the flux vector (mole m⁻² s⁻¹), in this case the flux in the porous particle, r the independent variable for the radius of the particle (m), R_(p) the radius of the particle, and n the normal vector to the particle surface.

To solve the equations above, the reaction term, R, has to be calculated. This implies the formulation of a new mass balance in micro scale. Such a mass balance is expressed by the equation below:

∇·(−D∇c′)+kc′ ^(Y)=0

Here, D′ is the effective diffusion coefficient in the particle, c′ is the concentration in the particle, and k the reaction rate constant for the heterogeneous reaction in the particle (mol^((γ−1))s⁻¹m^(3(γ−1))) In this case, transport takes place by diffusion only.

The diffusion-reaction equation, combined with the boundary conditions for the particle, give the concentration distribution in the particle.

−D′∇c′·n=0 at r=0

c′=εc

-   -   where ε denotes the porosity of the particle. This implies         symmetry in the middle of the particle. In addition, the         concentration at the surface of the particle is equal to the         concentration outside of the particle compensated by the fact         that part of the particle volume is occupied by solid catalyst         support.

The concentration distribution in the particle gives the flux at every point in the particles. This implies that the reaction term for the catalyst bed is given by the solution of the micro mass balance:

R=A _(p)(−D∇c′·n)

The complication in solving this system of equations is that the macro balance and the micro balance are defined in different coordinate systems. This problem is general for many chemical reaction engineering applications and is often solved by using analytical approximations of the solution to the micro balance. One possibility is to use Thiele modulus in the effectiveness value formulation. However, this approach cannot be used for complicated reaction mechanisms involving several reacting species. The solution exemplified here is general and can be used for very complex reaction mechanisms involving a large number of species.

-   -   Input data for the model are the following:

EXPRESSION VALUE D 1e−6 D 1e−7 c0 3 u 0 A_(p) 4e3 k 100 ε 0.6 R_(p) 1e−3 γ 1.5

Model Library Chemical_Engineering/Mass_Transport/packed_bed_reactor

Solving the Problem Using the Graphical User Interface

The approach here will be to model the bed as a 1-D model with independent variable x. At each x-coordinate there is also a model of one particle typical of all of the particles at that position in the packed bed. Since the particles are spherically symmetric and the surface concentration c is to all intents and purposes constant around each particle, a 1-D model with independent variable r can be used for each of the particles. In order to model particles for each position along the packed bed, many such 1-D models can be placed side by side creating effectively a 2-D geometry with independent variables x and r.

In this 2-D model all of the particles can be modeled independently. There is therefore a 2-D geometry for the particles and a 1-D geometry for the packed bed. Two couplings are used in the model. The packed bed concentration is used in the boundary condition for the particles and the flux at the surface of the particles is used in the reaction term in the packed bed.

-   -   Firstly switch to the Multiphysics window in the Model         Navigator. Select the 2-D, ChEM: Diffusion application mode.         Name the dependent variable c 1 whilst setting the independent         variables to x and r respectively. Press Add and select Solution         form: Weak.     -   Now choose a Weak, boundary constraint from the list, name the         dependent variable lambda and Add the mode. This mode is added         because coupling variables appearing in Dirichlet boundary         conditions should usually be handled with weak boundary         constraints.     -   Press the topmost Add button to select a new geometry. Use 1-D         as the dimension and press the top Add button once more.     -   Select the ChEM: Convection and diffusion application mode. Name         the Dependent variable to C and then Add the mode.     -   Select Solution form: Weak, Solver type: Nonlinear stationary         and press OK.

Draw Mode

-   -   Choose 1 Geom1: Diffusion (di) from the Multiphysics menu.     -   Draw a unit square with it's lower left corner at (0,0).

Mesh Mode

-   -   Select Parameters from the Mesh menu and enter 2e-1 in the Max         edge size, general field.     -   Press the More button and enter 3 1e-2 in the Max element size         for edges field. This makes the mesh very fine on boundary 3         which represents the outer surfaces of all of the particles,         near which the concentration changes rapidly. Press Remesh and         then OK.

Draw Mode

-   -   Choose 3 Geom2: Convection and Diffusion (cd) from the         Multiphysics menu.     -   Double click on the line and specify a geometry from 0 to 1.

Mesh Mode

-   -   Select Parameters from the Mesh menu, enter 2e-2 in the Max edge         size, general field, press Remesh and then OK.

Options and Settings

-   -   Enter the following variable names for use later, in the         Add/Edit Constants window under the Options menu.

NAME EXPRESSION gamma 1.5 D1 1e−7 D 1e−6 CO 3 k 100 epsil 0.6 Ap 1e3

p 1e−3 u 0.4

indicates data missing or illegible when filed Enabling the extended multiphysics couplings

-   -   First define a variable C_x to be available on boundary 3 in the         particle geometry (the outer surfaces of the particles) to be         equal to the packed bed concentration C at the corresponding         x-coordinate.     -   Open the Add/Edit Coupling Variables dialog under the Options         menu.     -   Enter C_x in the Variable name edit field and select extrusion         from the Variable type drop-down menu. Then press Add.     -   Switch to the Source tab and select the Geometry Geom2 at the         subdomain Level. Then select 1 in the window.     -   Enter C in the Expression field and enter x for the Local mesh         transformation coordinate x.     -   Switch to the Destination tab, select Geom 1 for the Geometry,         boundary for the Level and choose boundary 3. Enter x in the         Evaluation point transformation x field.     -   Press Apply.     -   Now define a variable Ndotn_x to be the normal surface flux for         the particles at position x, and make this variable available in         the packed bed geometry.     -   Switch back to the Variables. Referring to FIG. 83, name the         variable Ndotn_x and choose extrusion for its Variable type,         then press Add.     -   Go to the Source tab and select Geom1 at the boundary Level.         Select boundary number 3 and enter D1*cir/rp as the Expression         and x as the Local mesh transformation x coordinate.     -   Switch to the Destination tab and select Geom2 for the Geometry         at the subdomain Level. Select 1 and enter x as the Evaluation         point transformation x.     -   Press OK and the coupling variables have been defined.

Subdomain Mode

-   -   Choose 1 Geom1: Diffusion (di) from the Multiphysics menu.     -   Enter subdomain settings according to the following table.

SUBDOMAIN 1 D₁ (anisotropic) 0 0 0 (D1/rp {circumflex over ( )}2) * r{circumflex over ( )}2 R_(i) −k * r{circumflex over ( )}2 * c1{circumflex over ( )}gamma

-   -   Note that the diffusion is only in the r direction because the         2-D geometry is not a physically 2-D domain, merely a more         efficient way of handling a large number of 1-D models set one         beside the other.

Boundary Mode

-   -   First select Insulation/symmetry conditions for boundaries 1, 2         and 4. The third boundary should be a Concentration boundary         with epsil*C_x as its value.     -   Switch to the second Multiphysics mode: 2 Geom1: 1 variable weak         constraint mode (w1). Open the Boundary Settings dialog and         select boundary 3. Make it Active in this domain by selecting         this checkbox and enter c1 as the Constraint variable. Press OK         to make it active.

Subdomain Mode

-   -   Choose 3 Geom2: Convection and Diffusion (cd) from the         Multiphysics menu.     -   Enter subdomain settings according to the following table.

SUBDOMAIN 1 D₁ D R_(i)

Ap * Ndo

_x u u

indicates data missing or illegible when filed

Boundary Mode

-   -   First select a Convection>>Diffusion condition for boundary 2.     -   Boundary 1 should be a Concentration boundary with CO as its         value. Finish by pressing the OK button

Solve Problem

-   -   Press the Solve button to start the simulation.         Post mode     -   The default plot will give the view of the concentration         depicted in FIG. 84.     -   For the particles (Multiphysics 1) it is interesting to see a         contour plot. Open the Plot Parameters dialog. Deselect the         Surface plot and instead select Countor plot, then switch to the         Contour tab. Specify x as the Contour expression and         concentration of c1 (c1) as the Height expression. Enter 40 in         the Contour levels field and deselect the Color bar. The effect         of this is to lay 40 lines across the geometry at 40 different         x-coordinates and show the concentration distribution along each         line. Each one therefore represents the concentration         distribution within a single particle. It is also interesting to         see how the value of the normal flux which is a multiple of c1r,         changes as x changes, so switch to the Line tab and activate the         line plot. Enter c1r in the Line expression field and c1r/20 in         the Z expression field and press OK. The /20 is simply to         rescale the curve to be able to see it on the same axes as the         contour plot. The following plot results are shown in FIG. 85.

Turning now to FIG. 98, an exemplary aspect of a GUI 9810 for a design system is illustrated that includes a settings window 9820 displaying, for example, menu(s) for accessing multiphysics model settings associated with a linked multiphysics modeling system 9830. The design system is configured to interact with the multiphysics modeling system 9830 by accessing settings for forming and solving the multiphysics problems defined in the multiphysics modeling system 9830. For example, the GUI 9810 may allow the design system to access the multiphysics model setting including such items as the physical properties and boundary conditions of the system being modeled in the multiphysics modeling system 9830. The design system may be configured to access the boundary condition selection 9850 in the multiphysics modeling system 9830 from a face selection in the design system's user interface 9810. Similarly, selection of a body or part in the geometric representation in the design system's user interface 9810 may access physical quantities and physical properties associated with a geometrical domain 9840 modeled in the multiphysics modeling system 9830. It is contemplated that in certain embodiments access of the various physical quantities, physical properties, and boundary condition settings may be initiated through user selections of domains (e.g., bodies or parts) and faces via the GUI 9810 of the design system.

As illustrated in FIG. 98, the GUI 9810 may also include a geometric representation 9860 of a geometrical domain of at least a portion of a system being modeled in the multiphysics modeling system 9830. The window 9820 in the GUI 9810, used for accessing the multiphysics model settings, may include a display of menus that describe settings for physical properties and boundary conditions in a multiphysics problem. The settings in the menu 9820 may be associated with entities in the geometrical domain, such as domains, faces, edges, or vertices associated with the system(s) being modeled, and residing in the multiphysics modeling system. It is contemplated that selections of the multiphysics settings via the window 9820 on the GUI 9810 may implement routine(s) that describe the geometric entities and settings for the model attributable to a particular selection. In certain embodiments, the design system may be configured for developing or assigning various geometric properties and physical properties of a system. The design system may then interface with and/or send the different geometric representations, the selection of entities (e.g., domains, faces, edges, or vertices), and other setting to the multiphysics modeling system for subsequent multiphysics modeling, which may include processing of the data sent from the design system. It is also contemplated that it may be desirable for the multiphysics modeling system 9830 to send a solution or modeling result configurable for display on the GUI 9810 of the design system.

In certain embodiments, the design system and the multiphysics modeling system may reside in one or more memories, one or more processors, and/or one or more computer readable media associated with the same computer system. In other embodiments, the design system and multiphysics modeling system may reside in different computer systems connected over a local area network or a wide area network.

Referring now to FIG. 99, an exemplary aspect is illustrated of communications via a bidirectional link between a design system and a multiphysics modeling system. The communications are described in the context of non-limiting exemplary dynamic link communications that may be included in a bidirectional link between a design system (e.g., a computer-aided design system or CAD system) and a multiphysics modeling system. The bidirectional link may be in the form of computer code embedded in a memory or another computer readable medium. In certain exemplary embodiments, a CAD system user interface may be used to describe a multiphysics problem or design in the multiphysics modeling system. The multiphysics modeling system may seek a geometric representation from the CAD system to generate a geometrical domain for the multiphysics problem.

In certain methods of communication between a design system and a multiphysics modeling system, a design system 9910 may detect the installation of a multiphysics modeling system 9920, and in response, implement design system dynamic link library file(s) 9930 to facilitate communication with the multiphysics modeling system 9920. In addition, the multiphysics modeling system can implement multiphysics-related dynamic link library file(s) 9940 to facilitate communication with the design system 9910. In one exemplary embodiment, the dynamic link library files 9930, 9940 may be used to implement various commands related to geometric features between the design system 9910 and the multiphysics modeling system 9920. For example, the design system 9910 may be instructed to transfer geometric representations 9950 to the multiphysics modeling system 9920. In certain embodiments, the design system 9910 may'also transfer material properties, which may be stored in the geometric representations of the design system 9910. It is also contemplated that in certain embodiments, the design system 9910 may mesh the geometry and send the resulting mesh to the multiphysics modeling system 9920 as the geometric representations. It is also contemplated that in certain embodiments, the multiphysics modeling system 9920 may be configured to search, detect, and load the multiphysics dynamic link library files 9940 to allow communication with the design system. In addition, the design system's dynamic link library files 9930 may return the name corresponding to an installed design system 9910. The loaded dynamic link library files 9930, 9940 may include instructions for communicating commands between the multiphysics modeling system 9920 and the design system 9910.

It is contemplated that the multiphysics modeling system 9920, design system 9910, and the bidirectional link may be executed in computer system having a memory associated with a single processor or in a computer system having one or more memories associated with one or more processors. In certain embodiments, the multiphysics modeling system routine(s) may operate on one computer system, the design system routine(s) may operate on a second computer system, and the bidirectional link may operate on one or both of the computer systems. It is also contemplated that the bidirectional link may operate on a third computer system and that the multiphysics modeling system 9920 and the design system 9910 communicate through the third computer system via the bidirectional link. It is contemplated that communications between all the computer systems may occur asynchronously or synchronously. For configurations having multiple computer systems and/or multiple memories, communications between the various computers may occur over local connections or a local area network. It is also contemplated that communications between the various systems may occur over a wide area network. It is further contemplated that communications between the various systems may occur wirelessly. In certain embodiments, the bidirectional link includes a series of instructions stored in a memory and executed by a processor. It is also contemplated that the bidirectional link may comprise dedicated computer hardware having the instructions permanently stored in a memory and communications ports for receiving connections from the multiphysics modeling system and the design system computer(s) that allow communications of geometry and parameter data between the multiphysics modeling system and the design system.

FIG. 100 illustrates an exemplary aspect of a GUI 10000 that may be used to establish a bidirectional link, such as the link described in FIG. 99. The GUI may be displayed on a display associated with a multiphysics modeling system and can include various selectable icons that, when selected, implement different operations for the multiphysics modeling system. For example, the selection of the “LINK WITH CAD SYSTEM” icon 10015 may be configured to implement a series of instructions that establish a bidirectional link between the multiphysics modeling system and a computer-aided design system. For example, the “LINK WITH CAD SYSTEM” icon 10015 can be associated with and form a link between the geometric operations of the multiphysics modeling system and a design system, similar to the relationship illustrated in FIG. 99. While the icon(s) illustrated in FIG. 100 may be displayed or associated with other operations of the multiphysics modeling system, the relationships of geometry sequence(s) 10010 and geometric operations of a design system can often be logically associated with the geometric aspects of a physical system that may be the subject of multiphysics modeling. The geometry sequence icon 10010 illustrated in FIG. 100 can be configured to include the geometric objects and geometric operations that define the geometrical domain of the multiphysics modeling system, and can further allow these geometric aspects to be communicated to or from the design system once the link between the two systems is established. In one exemplary aspect, some parts of the geometrical domain may be entirely generated in the multiphysics modeling system, such that selection of icon 10015 is associated with and forms a link with geometric operations for other parts generated in the design system. For example, a screw part may be generated in a CAD system, but a nut associated with the screw may be generated in a geometry tool of the multiphysics modeling system. Then, by selecting icon 10015, the link between the design system and modeling system is established and geometric aspects of the screw may be transmitted to the multiphysics modeling system, and the geometric aspects of the nut may be transmitted to the CAD system.

Referring now to FIG. 101, a flowchart for an exemplary aspect of a bidirectional link using dynamic link library (“.dll”) files is described. The flowchart includes a multiphysics modeling system .dll 10140 and a design system .dll 10130, similar to the multiphysics system .dll 9940 and design system .dll 9930 discussed above for FIG. 99. As discussed previously, the dynamic links may be used to send commands from a multiphysics modeling system via the multiphysics modeling system's .dll to the design system. For example, a command may ask for the name and status of installed design systems. This is illustrated in step 10142 where the multiphysics .dll 10140 may send a request to a detected design system .dll to return the name and status of the design system. Upon the detection of the installed design system at step 10132, the design system .dll 10130 may at step 10134 send the name and status of the installed design system back to the multiphysics .dll 10140. At step 10144, the multiphysics .dll 10140 may send the status message from step 10134 to the multiphysics modeling system and then proceed to step 10146 where the multiphysics modeling system may send a command to the multiphysics .dll 10140 that includes, for example, a list of parameters describing geometric features of a physical system being modeled by the multiphysics modeling system. Proceeding from step 10146 to 10136, the multiphysics .dll 10140 in turn relays the command to the design system's .dll 10130 and then further to the design system where the command may be executed. At step 10138, a confirmation may be received by the design system .dll 10130 from the design system. Proceeding from steps 10138 to 10148, the design system .dll 10130 may send a confirmation back to the multiphysics .dll 10140 regarding the status of the executed command, which in turn may be communicated to the multiphysics modeling system. As illustrated in the example of FIG. 101, when steps in the bidirectional link are executed, a command involving a change, for example, in a geometric feature in the design system can automatically cause the design system to regenerate the geometric representation, which may be generated as a file containing the geometric representation (e.g., a Parasolid® file, a CAD file, a SolidWorks® file). The file containing the geometric representation may be automatically loaded by the multiphysics modeling system and the geometric operation in the geometry sequence and the geometrical domain may then be updated. In certain aspects, the geometric representation may also be updated in a design system user interface linked to the multiphysics modeling system.

It is contemplated that the bidirectional link between the multiphysics modeling system and the design system may be directly connected such that the detection step may not be necessary or may be simplified. For example, the name or identification of an installed design system may be known or directly stored in the bidirectional link, such that, for example, step 10134 can be removed from the aspect described in FIG. 101. It is also contemplated that alternate or modified configurations of the detection aspects may be desirable. For example, a setting defining the name and version of an installed design system may be entered by a user, or other wise received, in the multiphysics modeling system before a connection is made to the bidirectional link.

Referring now to FIG. 102, an exemplary aspect of a bridge connection 10210 is illustrated between a design system 10220 and a multiphysics modeling system 10230. A bridge connection, such as the one illustrated in FIG. 102, can communicate inputs and outputs between two systems in conjunction with operations associated with, for example, a window having selectable elements in a GUI. In one embodiment, the bridge connection may be associated with the display of a settings window in a design system GUI for a multiphysics model system that is connected via the bridge connection to the design system. Operations performed in the settings window of the GUI, such as selections from a pointer and/or keyboard events, can be sent via the bridge connection to the multiphysics model system. In certain embodiments, a bridge connection can also send information to the multiphysics modeling system for selections in a display window in the design system GUI associated with geometric representations of the system being modeled. In certain embodiments, the multiphysics modeling system can then send information associated with the selected geometric entity back to the settings window for the multiphysics modeling system that is displayed in the design system user interface.

The bridge connection 10210 in FIG. 102 is configured to communicate commands associated with settings of a multiphysics model. The bridge connection 10210 may be activated via a user selection from a window in the design system's user interface (e.g., see FIG. 98). In certain embodiments, the bridge connection 10210 may be automatically activated upon the implementation or execution of the computer-implemented instructions of the design system 10220. It is contemplated that in certain embodiments, the design system 10220 may detect the installation or execution of the computer-implemented instructions for the multiphysics modeling system and based on that detection activate the bridge connection 10210. It is also contemplated that the design system 10220 may be configured to start a process that executes the computer-implemented multiphysics modeling system 10230.

The bridge connection 10210 can be configured so that a GUI in the multiphysics modeling system 10230 communicates or interacts with a design system user interface. The design system's user interface may include a window that displays, for example, the multiphysics modeling system's model tree (see, e.g., FIGS. 103 and 110-120) and/or a window corresponding to the settings of a node for the model tree. Exemplary aspects of a model tree are presented in more detail in FIGS. 103 and 110-120. In certain embodiments, a model tree associated with the multiphysics modeling system that is displayed in a GUI can include the display of nodes that represent modeling operations and the display of branches that represent the logical relationships between the nodes.

It is contemplated that in certain embodiments the bridge connection may allow certain user input events 10222, 10232 such as mouse events, keyboard events, or other user input, to be sent from the design system's user interface to the multiphysics modeling system's model tree and/or a settings window displayed in the design system's user interface. The multiphysics modeling system 10230 may also send commands through the bridge connection 10210 to the design system 10220 using the design system's application programming interface (“API”). For example, the bridge connection 10210 may allow the multiphysics modeling system 10230 to render its graphics inside a graphics window in the design system's user interface. The design system's user interface may then display a view of a model geometry associated with the setup of a multiphysics problem. Selections 10224, such as those of geometric entities (e.g., domains, boundaries, edges, vertices) can also be requested from the design system's geometry by the multiphysics modeling system via the bridge connection 10210. User selections and/or selection results 10234 of geometric entities can be sent back and forth, through the bridge connection 10210, between the multiphysics modeling system 10230 and the design system 10220.

In certain embodiments, the multiphysics modeling system's settings window(s) are configured to receive selection settings from the design system 10220 through the bridge connection 10210. As discussed above, the multiphysics modeling system 10230 may receive user inputs 10232, such as mouse events and keyboard events, through the design system's user interface. In certain embodiments, the multiphysics modeling system 10230 may be configured via rendering command(s) 10236 to render graphics directly in a graphics window 10226 of the GUI of the design system 10220. This rendering of graphics may occur in response to a request from a user to show the results from the solution to a multiphysics problem or model. In certain embodiments, the multiphysics modeling system 10230 may receive the rendering request from the earlier described user inputs 10232 (e.g., mouse events or keyboard events).

FIG. 103 illustrates an exemplary aspect of a bridge connection for executing portions of a multiphysics modeling system GUI within a design system user interface. The bridge connection may be established between the design system and the multiphysics modeling system in response to a request for such a connection being sent from the design system to the multiphysics modeling system. Once a bridge connection is established, a design system user interface 10310 may also display a settings window 10314 having a model tree 10322 associated with model(s) from a multiphysics model system 10320. In one embodiment, the model tree 10322, in association with the bridge connection, can directly allow for user inputs into the multiphysics model system 10320 via the design system user interface 10310.

The model tree 10322 can include nodes 10324 (e.g., Materials, Mesh 1) containing references 10326 to settings (e.g., Joule Heating, Electromagnetic Heat Source, Electric Insulation, Thermal Insulation, Initial Values, Electric Potential, Temperature, Convective Cooling) of a multiphysics model and branches displaying relations between nodes. For example, a setting can include a description for a physical quantity, a physical property, or a boundary condition associated with the model. Model tree 10322 illustrates an exemplary setting of a boundary condition for convective cooling at a face of a multiphysics model. The model settings for the face include an external temperature and a heat transfer coefficient. In certain embodiments, a user of the design system can enter or select a node or face of the system being modeled from a geometrical display window 10312 in the design system user interface 10310. The entering or selection of a node or face can then send an instruction, via the bridge connection, from the design system to the multiphysics model system to display in the settings window 10314 for the selected node. The multiphysics modeling system 10320 can then send, again, via the bridge connection, a representation of the settings window for display in the design system user interface 10310.

Certain settings may be associated with geometric entities of the model, such as a face for a boundary condition, and the multiphysics modeling system may prompt or send an instruction to the design system requesting the selection of the geometric entity associated with the setting. The prompt or request may occur using similar operations described previously in FIGS. 98-102. In response to the entity selection, the design system user interface 10310 can then generate a corresponding geometric entity in the multiphysics modeling system 10320. The representation of the geometric entity can be displayed in the design system user interface 10310, such as in the geometrical display window 10312 or in a window associated with a selected node or face. The settings, of an entity can be entered as instructions using the settings window 10314. The instructions can include one or more selections of default or custom items from the settings window 10314. The selections may occur via user input received through a mouse, keyboard, or other user input device. In certain embodiments, the settings may be expressions entered using a keyboard or the setting may be predefined and selected from a window listing one or more of the predefined expressions. The input instructions can then be sent or transferred to the multiphysics modeling system 10320. Based on the instructions received from the design system, the multiphysics modeling system may then interpret the instructions and execute commands for forming the components of the multiphysics model described by the settings. The multiphysics modeling system 10320 can then transmit the status of the executed setting(s) back to the design system, including, for example, any updates to geometrical display window 10312.

The bridge connection can facilitate any of several exemplary associations and/or communications between the multiphysics modeling system 10320 and the design system, such as those illustrated in FIG. 103. For example, boundary conditions selections 10328, including physical quantities and properties, may be received by the multiphysics modeling system 10320 from the design system. FIG. 103 illustrates the receipt by the multiphysics modeling system 10320 of boundary condition selections 10328 including, for example, face selections, convection cooling settings, and heat flux quantities for a model, via the design system user interface 10310. Furthermore, a user interface 10329 associated with the multiphysics modeling system 10320 may receive selection data via the boundary conditions selection(s) 10328 and in turn communicate the boundary condition(s) data via the bridge connection back to the design system, which then displays updated information on the design system user interface 10310. The multiphysics modeling system 10320 may also determine various results based on the boundary condition selection(s) and also communicate those results for the multiphysics model to the design system, which can display the results on the design system user interface 10310. The communicated results can also be based on any physical entity or physics quantity associated with the system being modeled. That is, FIG. 103 illustrates the interactive nature and/or exchange of information between a design system (e.g., 9810, 9910, 10220, 10310) and a multiphysics modeling system (e.g., 9820, 9920, 10230, 10320) and how information may be displayed to a user on a GUI (e.g., 9810, 10310) associated with a design system that is bridged to a multiphysics modeling system (e.g., 9820, 10320).

Other boundary condition selections are contemplated in addition to those described above. For example, in a model having electromagnetic properties and quantities, boundary condition selections can include ground, current density, electric potential, distributed impedance, reflecting, absorbing, port, perfect electric conductor, etc. In a model having structural mechanics properties and quantities, boundary condition selections can include fixed constraint, roller, load, contact, displacement, free, etc. In a model having fluid properties and quantities, the boundary condition selections can include inlet, outlet, wall, free surface, pressure, etc. The foregoing boundary condition selections are non-limiting examples of domain settings and boundary conditions that can be selected and for which information can be exchanged between a design system and a multiphysics modeling system. It is contemplated that these and other types of domain settings and boundary conditions would be understood to be exchangeable between the systems depending on the scientific and engineering principles desired to be modeled.

Referring now to FIG. 104, an exemplary aspect of the present disclosure is illustrated for dynamically controlling, via a bidirectional link and a bridge connection, parametric and geometric features in a design system. The steps shown in FIG. 104 can be implemented via a multiphysics modeling system GUI that is executed or displayed in a design system user interface, similar to the user interface illustrated in FIG. 103. The steps shown in FIG. 104 include a series of steps between the design system 10410 and the multiphysics modeling system 10420 occurring over a communications path, such as the bidirectional link and bridge connection described elsewhere herein.

Turning now to step 10452, a window or list of parameter definitions may be generated by the multiphysics modeling system 10420 and transferred to the design system 10410. These communications may be facilitated via dynamic link library files described elsewhere herein. At step 10454, the parameter definitions are received and may be displayed and/or accessed via the design system user interface. In certain embodiments, the display of the parameter definitions may occur as a multiphysics modeling system GUI displayed inside the design system's user interface. At step 10456, the list of parameters or parameter definitions may be received as instructions, sent via the bridge connection from the design system 10410 to the multiphysics modeling system 10420. At step 10456, the multiphysics modeling system 10420 may interpret the list or definitions before sending them to the design system. For example, the multiphysics modeling system may interpret the parameter definition to be associated with geometric features. It is also contemplated that in certain embodiments material properties may be obtained from the design system. At step 10458, the design system 10410 may receive parameters that are identified as parameters controlling geometric features. The geometric features can then be updated in the design system according to the parameter definitions or values received from the multiphysics modeling system. At step 10460, the design system may update a geometric representation of the model based on the updated geometric features. Furthermore, the design system may also generate a file containing the geometric representation based on the updated geometric features. At step 10462, the generated file in step 10460 may be received or loaded into the multiphysics modeling system and a representation of the geometrical domain of the model can be updated. At step 10464, the multiphysics modeling system 10420 may then solve a multiphysics problem using the updated geometrical domain for the system being modeled. At step 10456, the design system can receive results or solutions associated with the geometrical domain, where the results or solution are determined from the file received at step 10462. The results or solution can then be displayed in the design system's user interface.

Referring now to FIG. 105, another exemplary method is illustrated for dynamically controlling, via a bidirectional link, parametric and geometric features between a design system and a multiphysics modeling system. At step 10556, a list of parameters or parameter definitions as defined by the multiphysics modeling system may be sent from the multiphysics modeling system 10520 to the design system 10510 through a bidirectional link, as illustrated and discussed, for example, in the context of FIGS. 99-102. At step 10558, these parameters are received by the design system 10510 and may be identified by the design system as parameters controlling geometric features of the model. The geometric features can then be updated in the design system according to the parameter definitions or values received from the multiphysics modeling system. For example, the value of a radius of a fillet associated with the face of a model may be controlled or altered. At step 10560, the design system may update a geometric representation of the model based on the updated geometric features. Furthermore, the design system may also generate a file containing the geometric representation based on the updated or altered geometric features. At steps 10561 and 10562, the generated file in step 10560 may be automatically received or loaded into the multiphysics modeling system and the representation of the geometry sequence and geometrical domain of the model can be updated. In certain embodiments, selected aspects of the parameter definitions from step 10556 may be directly sent to steps 10561 and 10562, such as parameter definitions that are unchanged (e.g., parts of the geometry that are not changed) and thus do not necessarily need to be sent to the design system. At step 10564, the multiphysics modeling system 10520 may then solve the multiphysics problem using the updated geometrical domain for the model.

FIG. 106 illustrates another non-limiting exemplary aspect of the present disclosure for dynamically controlling, via a bidirectional link, parametric and geometric features and associativity operations to set physical properties and boundary conditions in a multiphysics modeling system. The associativity operation at step 10663 is used to set the physical properties and boundary conditions in the multiphysics modeling system 10620. Beginning at step 10656, a list of parameters or parameter definitions as defined by the multiphysics modeling system may be sent from the multiphysics modeling system 10620 to the design system 10610 through a bidirectional link, as illustrated in discussed, for example, in the context of FIGS. 99-102. At step 10658, these parameters are received by the design system 10610 and may be identified by the design system as parameters controlling geometric features of the model. In certain embodiments, the received parameters may control already existing geometric features. The geometric features can then be updated in the design system according to the parameter definitions or values received from the multiphysics modeling system. At step 10660, the design system may update a geometric representation of the model based on the updated geometric features. Furthermore, the design system may also generate a file containing the geometric representation based on the updated or altered geometric features. At steps 10661 and 10662, the generated file in step 10660 may be automatically received or loaded into the multiphysics modeling system and the representation of the geometry sequence and geometrical domain of the model can be updated. In certain embodiments, selected aspects of the parameter definitions from step 10656 may be directly sent to steps 10661 and 10662, such as parameter definitions that are unchanged and thus do not necessarily need to be sent to the design system.

In certain embodiments, the method of FIG. 106 may proceed directly to step 10664, where the multiphysics modeling system 10620 solves the multiphysics problem using the updated geometrical domain for the model. However, the multiphysics modeling system 10620 may instead proceed from step 10662 to step 10663 where the multiphysics modeling system may use associativity to reuse settings for the physical properties and boundary conditions from a previous formation of a multiphysics problem and apply those reused settings for the formation and solution of the multiphysics problem using the updated geometrical domain. The associativity operation at step 10663 may include mapping geometric entities (e.g., domains, faces, edges, vertices) between the old or previous geometrical domain and the new geometrical domain. The geometrical domain may be defined by a geometry sequence containing geometric objects and geometric operations. For example, a new geometric object (e.g., parent object) may be constructed from a number of child geometric objects (e.g., a number of other geometric objects). For each such parent, there may be a mapping between geometric entities in the parent object and in the child object. In particular, when a new geometric representation is loaded into a multiphysics modeling system through a bidirectional link, the bidirectional link may provide such a mapping between the geometric entities of the old object and the new object. This mapping may be constructed by asking the design system for the mapping between the geometric entities. It is contemplated that during the updating of the geometrical domain, some or all selections of geometric entities may be updated by applying the mapping between geometric entities of the old and the new geometrical domain. This mapping may be used to set physical properties and boundary conditions for the multiphysics problem.

A preliminary step in the associativity mapping process may include finding a minimal set of common ancestors of the old and the new finalized geometrical object. A next step may be to compute mappings of geometric entities from the common ancestors to the geometric objects, for example, by composing the mappings for the chain of parents or ancestors relating the objects. The mappings may then be composed to get a mapping from the new finalized geometrical domain to the old geometrical domain. The mapping may then be improved by applying some experience-based techniques that are based on adjacencies between entities of different dimensions. An example of the associativity mapping process may include having an object that is the result of a change that is done on an original object. The resulting object would have the original object as an ancestor such that the resulting object inherits the settings of the original object or ancestor. For example, if the original object were a rectangle, the change could be rounding one of the corners of the rectangle. In the associative mapping process, the multiphysics modeling system can map the exemplary boundary conditions from the original rectangle to the rectangle with the rounded corner. Next, another change can be made to the object, such as rounding another corner of the rectangle. Further applying the associative mapping process, the multiphysics modeling system can then map or track from the first rectangle with one rounded corner up to the ancestor without rounded corners and then down to the rectangle with the two rounded corners. Thus, by this process of associativity mapping, the multiphysics modeling system can track objects up and down a geometry sequence in order to relate physical settings to new objects that may reuse portions of the original geometry sequence.

It is contemplated that in certain embodiments the method of FIG. 106 may be used for a multiphysics problem to optimize a value of a parameter associated with a geometric feature. The value may be optimized using an objective function that accords with certain design criteria for the product being modeled or optimized. For example, the multiphysics modeling system may use an optimization algorithm to search for an optimal value based on the objective function. As the search for the optimal value progresses, the optimization algorithm may need to evaluate an objective function for updated parameter value(s). The updated value(s) can then be sent back to a design system, which may then update a geometric representation. The updated geometric representation may then be used by the multiphysics modeling system to update the geometrical domain. The multiphysics modeling system can then compute a new solution to the multiphysics problem along with new update(s) to the parameter value(s) based on the updated geometrical domain. The multiphysics modeling system can then determine whether to repeat the process based on the initial design criteria. That is, as illustrated between steps 10664 and 10656, the iterative process or loop can be repeated a single time or as many times as is necessary to meet the design criteria and that can be supported by the computing capabilities of the multiphysics modeling system processor(s).

Referring now to FIG. 107, an exemplary GUI is illustrated for the multiphysics modeling system that may be displayed for dynamically controlling features between the multiphysics modeling system and a design system via a bidirectional link. The GUI may include parameter names (e.g., Rad1) and their associated values (e.g., R1). The parameter names are shown to be defined in a settings window that may be accessed by selecting a feature or icon from the graphical representation of the bidirectional link in the multiphysics modeling system. The parameter names may refer to names of parameters that control geometric features in the design system. The geometric features in the design system may then be updated according to the parameter values in the multiphysics modeling system by selecting an icon associated with a synchronize feature between the multiphysics and the design systems.

It is contemplated that in certain embodiments it may be desirable to define variations for parameters that control, for example, the geometric features of a model. Referring now to FIG. 108, an exemplary embodiment is illustrated for defining variations for parameters that control geometric features in a design system. The variations are defined via a multiphysics modeling system 10820 that is in communication with the design system 10810 through a bidirectional link. In certain embodiments, a bidirectional link may be complemented by a bridge connection that allows a multiphysics modeling system to be accessed from a window in a design system GUI, as described elsewhere herein.

At step 10852, a window for entering parameter list(s) may be generated by the multiphysics modeling system 10820 and transferred to the design system 10810 through the bidirectional link. For example, parameters describing geometric features, such as a radius or length, or material properties, such as tensile strength or density, associated with a detail of a model may be generated and transferred through the bidirectional link. At step 10854, the parameter lists defined or entered are received and may be displayed in the design system user interface. In certain embodiments, the display of the parameter definitions may occur as a multiphysics modeling system GUI displayed inside the design system's user interface. The lists may be received as instructions, and in certain embodiments, these instructions may be sent via the bridge connection of a bidirectional link from the design system 10810 to the multiphysics modeling system 10820. The list or definitions may be interpreted before being sent to the design system. For example, the multiphysics modeling system may interpret the parameter definition to be associated with geometric features. In certain embodiments, the interpretation of the lists may be completed in the design system. Each list of parameters may represent a variation of parameter values to be used in solving a model. At step 10858, the parameters are identified as parameters controlling geometric features. The geometric features can then be updated in the design system according to the values of the parameters in each list. At steps 10860 a, 10860 b, 10860 c, the design system updates geometric representations for each list of parameters for the model variations based on the updated geometric features. Furthermore, the design system may also generate a file for each list of parameters, where each file contains the corresponding geometric representation. At steps 10862 a, 10862 b, 10862 c, each generated file in step 10860 a, 10860 b, 10860 c may be received or loaded into the multiphysics modeling system and representations of the geometrical domains of the model variations can be updated. At step 10864 a, 10864 b, 10864 c, the multiphysics modeling system 10820 may then solve the multiphysics problems using the updated geometrical domains for the system variations being modeled. At steps 10866 a, 10866 b, 10866 c, the design system receives the results or solutions associated with each of the geometrical domains determined from the files received at steps 10862 a, 10862 b, 10862 c. The multiphysics modeling system can create one solution set for each variation of the geometrical domain. The solutions can then be displayed in the design system's user interface. On the lower end, it is contemplated that as few as two variations can be modeled and results be determined. On the upper end, while only three geometric representations and domains are illustrated, this is for example purposes only. That is, more than three lists of parameters and geometric representations and lists of parameters can be input into the systems described herein such that a user can determine the desired model variations.

It is contemplated that in certain embodiments, the multiphysics modeling systems described herein may use the concept of associativity to set the physical properties and boundary conditions specified for one geometrical domain and reuse these settings for each variations of the geometrical domain. Associativity may be achieved by mapping geometric entities (domains, faces, edges, vertices) between an old or previous geometrical domain and a new or to-be-varied geometrical domain. When the new or varied geometric representation is received or loaded into the multiphysics modeling system through a bidirectional link, the bidirectional link may provide the mapping between the geometric entities in the old object and the new or varied object. In certain embodiments, this mapping may occur by the multiphysics modeling system prompting or requesting the design system for the physical properties and boundary conditions from the old object. When updating the geometrical domain, all selections of geometric entities can be updated by applying the mapping between geometric entities in the old and the new geometrical domains. The mapping may then be used to set physical properties and boundary conditions for a multiphysics problem that is to be solved by the modeling system. The multiphysics modeling system can then solve the problem using each of the updated geometrical domains corresponding to the variations in geometric features. The multiphysics modeling system can then determine one solution dataset for each variation in geometrical domain. The solutions mapped on a corresponding geometrical domain can then be sent by the multiphysics modeling system to the design system, where the solutions are then displayed in the design system's user interface with each variation in geometrical domain.

Referring now to FIG. 109, an exemplary GUI is illustrated for defining variations of parameter(s) that control the geometric features in a design system, from a multiphysics modeling system, using a bidirectional link. In certain embodiments, the parameter names in the multiphysics modeling system may also refer to names of parameters that control the geometric features in the design system. The parameter values may be varied according to an interval having certain boundaries, such as a minimum value and a maximum value, plus an increment for values in between. Each parameter value may be contained in a separate parameter list in the multiphysics modeling system that is then sent to the design system for automatic synchronization and generation of the files that contain the design system's geometric representation for each variation. One exemplary aspect of the present disclosure includes a method for accessing settings for forming and solving multiphysics problems in a multiphysics modeling system from a design system user interface. The solution of a multiphysics problem is displayed in the design system user interface.

Another exemplary aspect of the present disclosure includes a method for establishing and maintaining a bidirectional link between a CAD system and a multiphysics modeling system for communicating commands involving geometric features.

Yet another exemplary aspect of the present disclosure includes a method for establishing a bridge connection between a CAD system and a multiphysics modeling system for communicating commands involving settings in a multiphysics problem.

A further exemplary aspect of the present disclosure includes multiphysics software (e.g., algorithms or instructions configured to be executed on a processor) that is able to run parts of its GUI inside a CAD system user interface using a bridge connection. The settings for a multiphysics problem, such as physical properties and boundary conditions, can be accessed from a representation of the multiphysics problem in the form of a model tree in the CAD system user interface.

Another exemplary aspect of the present disclosure includes a method for dynamically controlling the parametric and geometric features in a CAD system from parts of a multiphysics modeling system's GUI run in the CAD system user interface via a bidirectional link and a bridge connection. The parametric and geometric features of the CAD system are expressed in terms of parameters in the parts of the multiphysics modeling system that are accessed in the CAD system's user interface. The CAD system dynamically returns a geometric representation, which is automatically loaded by the multiphysics modeling system and a geometrical domain is changed accordingly. The multiphysics modeling system can be configured to define and solve the multiphysics problem for the geometrical domain. For example, a dynamic-link library (DLL) file may be used, which is an executable file that allows programs to share code and other resources necessary to perform particular tasks.

Yet another exemplary aspect of the present disclosure includes a method that defines a variation of a geometrical domain using sets of parameters that control the geometric features in a CAD system from parts of a multiphysics modeling system GUI run in the CAD system user interface via a bidirectional link and a bridge connection. The CAD system can return a modified geometric representation of the variations, which can be automatically loaded in the multiphysics modeling system. Each geometric representation corresponds to a variation and one geometrical domain is defined for each set of parameters. The multiphysics modeling system can then define and solve a multiphysics problem for each geometrical domain.

Another exemplary aspect of the present disclosure includes a method executed on a computer system for establishing a bidirectional link between a CAD system and a multiphysics modeling system. The method includes detecting one or more installed CAD systems, communicating commands between the multiphysics modeling system and the one or more CAD systems, and representing the bidirectional link as a geometric operation in a geometry sequence in the multiphysics modeling system.

In further exemplary aspects of the present disclosure, the method for establishing the bidirectional link includes loading dynamic link libraries for each of the detected one or more CAD systems. The dynamic link libraries can be used for communicating the commands. The method may further include using the commands to generate files containing a geometric representation in the CAD system. The method can additional include generating a geometrical domain in the multiphysics modeling system using the files containing the geometric representation and the geometry sequence. The method may further include defining a multiphysics problem using the geometrical domain.

In yet further exemplary embodiments of the present disclosure, the method for establishing bidirectional links can also include sending via the bidirectional link the parameters from the multiphysics modeling system describing geometric features in the CAD system. The method can also include sending via the bidirectional link the parameter lists representing variations in the geometric features. The method may further include specifying physical properties and boundary conditions in the multiphysics modeling system for each of the variations using associativity.

FIGS. 110-120 illustrate various exemplary aspects of a model tree including logical relationships between various exemplary nodes that may be included in a method for forming and solving a multiphysics problem in a multiphysics modeling system. It is contemplated that in certain aspects the model tree is presented in a GUI of a multiphysics modeling system, or in a window associated with the modeling system where the window is display in the GUI of a design system (see, for example, FIG. 98 or 103), such as a CAD system. A model tree can include selectable nodes, which when selected, display or allow input of different operations or parameters for the multiphysics modeling system. It is also contemplated that the results of different modeling operations can also be represented in nodes of the modeling tree.

It is contemplated that a model tree, such as in the exemplary aspects disclosed herein, can be desirable because it provides a graphical programming environment for developing multiphysics problems in a multiphysics modeling system. As discussed above and elsewhere herein, a model tree includes nodes and branches. The nodes represent various modeling operations and the branches represent the logical relationship between the operations represented by the nodes.

It is contemplated that it may be desirable to represent sequence(s) of modeling operations as nodes in a model tree. The model tree nodes may then be used to generate the constituents of a multiphysics problem that a user desires to model. The constituents of the problem being modeled can include, among other things, a geometrical domain, physical quantities, physical properties (e.g., mechanical, electrical, magnetic, thermal), boundary conditions, mesh, solver configurations, and results or solutions of the multiphysics model. In certain embodiments, a sequence of modeling operations may be structured to include one or more child nodes (e.g., subnodes) that branch from a parent node (e.g., primary node) representing a constituent of a multiphysics problem. The branches in the model tree can be used to represent the logical relationship between the parent and child nodes. For example, a system to be modeled may include one or more model nodes (e.g., a parent node) and under each of those model nodes there may be a geometry node, material node(s), physics node(s), and a mesh node (e.g., child nodes). Furthermore, one or more of the child nodes may also have their own grandchild nodes for adding contributions to the physical quantities associated with the associated child node.

It may also be desirable in a multiphysics modeling system to generate partial differential equations that describe certain physical quantities in a multiphysics problem. For example, in certain embodiments, a partial differential equation for a multiphysics problem may be generated by adding contributions to a system of partial differential equations rather than changing an existing set of generic system(s) of partial differential equations. Such a process can provide efficiencies to the generation of partial differential equations. In one exemplary aspect, operations may be included as nodes in the model tree for adding the contributions to the partial differential equations. The model tree may include a parent node for physics elements, and the parent node may include a child node or branch for adding contributions to the partial differential equations associated with the problem being modeled. A model tree and node approach can be desirable because it provides clarity to the user of the multiphysics modeling system during the set up and modification of the various constituents of the problem being modeled.

In a multiphysics modeling system it may further be desirable to add contributions to a multiphysics problem by attributing the added contributions to a geometrical domain. The benefit can include that contributions are only defined when needed and any generic equations, that by default are associated with all the geometric domains, do not need to be altered or removed.

In a multiphysics modeling system it may further be desirable to have a model tree that has nodes for more than one model (see, e.g., FIG. 120) such that several components in a system can be simultaneously modeled together. The individual models can share certain model inputs or parameters when the models are simulated simultaneously during the processing of a multiphysics problem.

Numerous exemplary and non-limiting aspects of a model tree for a multiphysics modeling system are discussed in more detail below. Furthermore, an exemplary multiphysics modeling system includes the COMSOL® 4.0 or COMSOL Multiphysics® simulation software operating on a computer system, as such software is available from COMSOL, Inc. of Burlington, Mass. Additional exemplary aspects of multiphysics modeling systems are described in U.S. patent application Ser. No. 10/042,936, filed on Jan. 9, 2002, now issued as U.S. Pat. No. 7,596,474, U.S. patent application Ser. No. 09/995,222, filed on Nov. 27, 2001, now issued as U.S. Pat. No. 7,519,518, and U.S. patent application Ser. No. 09/675,778, filed on Sep. 29, 2000, now issued as U.S. Pat. No. 7,623,991, each of which are hereby incorporated by reference herein in their entirety.

A model tree for a multiphysics modeling system can include a global definitions node for creating or inputting model parameters, variables, and function that have a global scope, and thus, are not specific to a particular model branch. The model tree can further include one or more model nodes, a study node, and a results node. The model node(s) can be used to set up a system or component to be modeled, and the input or set up can be done, for example, as a two-dimensional simplification of the component or system. Other exemplary model node(s) can be input or set up with a full three-dimensional description. The study node can be used to set up the simulation(s) of the whole multiphysics model or portions thereof, and can be applied for one or more models as set up using the model node(s). The results node can then be used to further investigate and review the solution received from the study node.

FIG. 110 illustrates an exemplary embodiment of a process for generating a model tree within a multiphysics modeling system. At step 11010, a window displayed on a GUI (e.g., a monitor) can be configured to allow the system user to select a space dimension for a model. For example, the user can choose from several selectable options or be allowed to provide inputs for the space dimensions of a model, including dimensions for three-dimensional, two-dimensional, two-dimensional axisymmetric, one-dimensional, one-dimensional axisymmetric, or zero-dimensional model(s). The selection or receipt of space dimension input(s) can then be used to determine and display a physics list at step 11020. The choices or options available on for a physics list can vary depending on the space dimension input(s) selected in step 11010. The physics list that is displayed in step 11020 can be displayed in a window of the GUI associated with the multiphysics modeling system. Each of the physics choice(s) or option(s) can include descriptions and equations for a variety of engineering or scientific disciplines, such as those described elsewhere herein (e.g., joule heating and thermal expansion, solid mechanics, electrical circuits), which can be modeled in the multiphysics modeling system. It is further contemplated that a user can input or define a customized physics for use in determining the solution to the model. At step 11030, a user may then select the desired one or more physics to be applied and simulated for the model(s). The selection of the physics at step 11030 determines a set of physical quantities associated with the received selection that are available for further manipulation in a multiphysics problem. The selection of the physics at step 11030 can also implement the selection of predefined studies and/or numerical preferences associated with a given physics. At step 11040, the system displays a study list, including one or more study options, in a window of the GUI. At step 11050, the user can select a study from the list displayed in step 11040. The various selections available in the study list can include, for example, stationary, time dependent, eigenfrequency, or some other study type that would be known in the field of the system being simulated in the multiphysics modeling system. Finally, at step 11060, the multiphysics modeling system can generate a model tree based on the input received from the system user via the model tree.

In certain embodiments, the selection of a space dimension in step 11010 can be used to determine the name(s) and icon(s) of model node(s) available in a model tree. The selection of the space dimension can further determine the content in the setting(s) that may be accessed in the model tree by a system user. In certain embodiments, the selection of physics at step 11030 can also determine certain default content of a physics branch in a model tree and the available setting in the different nodes. Further, it is also contemplated that the selection of the study at step 11050 may determine the content of one or several study steps that may be included in the study node.

Turning now to FIG. 111, an exemplary aspect of a process is illustrated for forming and solving a system of partial differential equations in a multiphysics modeling system based on operations represented in a model tree. The model tree for the multiphysics model that is generated, such as for the exemplary process illustrated in FIG. 110, can include a model node, a study node, and a results node. The model node may include a plurality of child nodes, such as a geometry node, material node(s), physics node(s), and mesh node(s). The study node can also include child nodes associated with solving the multiphysics problem.

At step 11110, a geometric representation is generated by the multiphysics modeling system based on operations associated with child nodes to the geometry node. For example, selection of the geometry node may display various child nodes that allow a user to execute additional operations associated with the geometry node and the generation of the geometric representation in step 11110. It is also contemplated that the geometry of the model or problem to be solved may be imported into the geometry node, such as from a computer-aided design file or through associations between a computer-aided design system and a multiphysics modeling system, as described elsewhere herein (see, e.g., 98-109).

At step 11120, physical properties are assembled by the multiphysics modeling system for the domains contained in the geometric representation generated in step 11110. These physical properties are associated with the materials node(s) in the model tree, which include the material properties for all the physics and all the domains in one or more model node(s). In certain embodiments, the materials node can include specific material(s) (e.g., cast iron, concrete, titanium) that are selectable by a user for the system(s) or component(s) being modeled. Depending on the complexity of the system being modeled, the system may have multiple components or elements each having different material properties that can be assembled in step 11120.

At step 11130, the multiphysics modeling system assembles the physics quantities and boundary conditions based on the representations of operations associated with one or more physics nodes of the multiphysics model. The assembled physics quantities and boundary conditions may be defined in the domains contained in the geometric representation using the physics properties determined from the operations represented in the materials node.

At step 11140, a mesh is generated by the multiphysics modeling system for the geometric representation and is based on the representations of the operations in the mesh node. For example, a system user may select to execute the mesh operations in a menu displayed by clicking or selecting the mesh node. In one exemplary and non-limiting embodiment, the system user may select to create an unstructured tetrahedral mesh for a component being modeled. Other non-limiting examples of mesh types may include prism, pyramids, swept, boundary layer, hexahedral, surface (e.g. for shells), and edge meshes (e.g., for beams). Other mesh geometries known in the field of the present disclosure are also contemplated.

Next, at step 11150, the multiphysics modeling system may proceed with the compilation and discretization of equations for all the study steps selected in the study node for each of the model(s). As discuss above, a study node may contain a representation of study steps for a solution to a set of partial differential equations. The study node can include child nodes for compiling the partial differential equations for each study step. Furthermore, the study node may include child nodes representing the discretization and solution sequence for the equations for each study step.

A system user may select to execute the operations represented by the child nodes in the study step from a menu (e.g., a drop-down menu) displayed after selecting the study node. The menu may be displayed by clicking on or selecting the study node as it is displayed in a GUI. The execution of the study steps may involve compiling a set of partial differential equations based on the physics quantities and boundary conditions generated by the physics, and based on the analysis selected for the study step, such as whether to implement a transient (e.g., dynamic) or stationary (e.g., static) analysis. The equations are discretized based on the meshed geometric representation. Then, at step 11160, discretized equations from step 11150 may be solved using a solver represented by child node(s) of the study node.

In certain embodiments, the multiphysics modeling system may be solving a multiphysics problem including a plurality of model nodes with corresponding geometry, materials, physics, and mesh child nodes. Furthermore, each of the plurality of model nodes may be used to generate a corresponding part of the set of partial differential equations in the multiphysics problem. It is contemplated that the complete set of partial differential equations may be compiled, discretized, and solved in steps 11150 and 11160, for different study steps, by solvers represented by child nodes to the study node. The compiling, discretization, and solving of the partial differential equations can be completed automatically through the execution of a series of processes in the multiphysics modeling system, without the need for any further user inputs.

At step 11170, the results of the solution to the multiphysics problem may be generated and displayed or otherwise output for later display or use. For example, the solution to a multiphysics problem may be visualized or prepared for display according to the operations represented by one or more child nodes associated with the results node. Such an operation may include the generation of one or more graphs of a set of results, which may be generated by clicking or selecting a results node that implemented a predetermined or customized set of operations for preparing the display of the results.

Turning now to FIG. 112, an exemplary aspect of a model tree 11200 is illustrated for forming and solving multiphysics problems in a multiphysics modeling system. In certain embodiments, the model tree 11200, or variations thereof based on different modeling features, is presented on a GUI associated with a processor configured to execute the multiphysics modeling system. It is also contemplated that model tree 11200 may be presented in a window on a GUI for a design system, where the window is associated with the multiphysics modeling system operating on the same or a different processor implementing routines associated with the design system.

Model tree 11200 may include different configurations and different features represented as logically arranged nodes associated with simulating a multiphysics problem. For example, a primary node 11210 (e.g., thermal_actuator_tem.mph) may represent the multiphysics problem for which a solution and results are desired. Node 11210 is exemplified to include four child nodes including global definitions node 11220 (e.g., Global Definitions), model node 11230 (e.g., Thermal Actuator), study node 11260 (e.g., Study 1), and results node 11270 (e.g., Results). Each of nodes 11220, 11230, 11260, 11270 may have their own additional child nodes, which in turn may also have their own respective child nodes, such that a branch of various logically associated nodes are built from the primary node 11210 for model tree 11200.

The exemplary child node (e.g., Parameters) branching from the global definitions node 11220 may represent operations that generate parameters, variables, and/or functions that apply to the entire multiphysics problem being solved, and thus, operations that are not generally attributable to specific geometric entities, domains, boundaries, edges, or vertices. The operations represented by the child nodes (e.g., Parameters) can be considered global to multiphysics problem represented in model tree 11200. For example, a parameter from the child node illustrated for node 11220 may be used to define a general physical constant and may be utilized in a plurality or even all the nodes in a model tree.

The exemplary child nodes (e.g., Definitions, Geometry 1, Materials, Joule Heating and Thermal Expansion, Mesh 1) branching from the model node 11230 (e.g., Thermal Actuator) may represent operations that generate a geometrical domain node (e.g., Geometry 1), physical properties node 11240 (e.g., Materials), physics node 11250 (e.g., Joule Heating and Thermal Expansion), and/or a mesh node (e.g., Mesh 1). In certain embodiments, the exemplary model node 11230 may generate partial differential equations for the mesh and/or the geometrical domain, or partial differential equations associated with the geometrical domain. The partial differential equations can be formed using the physical properties node 11240 and/or physics node 11250, which may include additional child nodes for physical quantities and boundary conditions. In the exemplary embodiment illustrated in FIG. 112, the physics node 11250 is described as Joule Heating and Thermal Expansion, though it would be understood that other engineering and scientific phenomena could be simulated, as well (e.g., acoustics, chemical reactions, diffusion, electromagnetics, fluid dynamics, geophysics, heat transfer, porous media flow, quantum mechanics, structural mechanics, wave propagation, microelectromechanical systems, semiconductor systems, plasmas).

Operations for solving the partial differential equations, such as those associated with the model node 11230, can be selected from child nodes branching from the study node 11260 (e.g., Study 1). The study node 11260 can include one or more study steps. For example, in a first study step (e.g., Step 1: Stationary 1), partial differential equations may be solved at stationary or static conditions while a second step may follow where these partial differential equations may be solved for time-dependent or dynamic conditions. The study node 11260 may therefore contain operations that add or remove terms in partial differential equations, according to how each step may be defined. It is also contemplated that a study node may include child nodes representing operations for solving partial differential equations using a finite element solver (e.g., Solver Configurations).

A branch from the primary node for a multiphysics problem can also include a results node 11270, which may further include additional child nodes representing operations for generating simulation results for solution(s) to the multiphysics problem that are transformable to a predetermined or customized format presentable to the user of a multiphysics modeling system. For example, the child nodes may include results presented in table formats, as derived values, as various multi-dimensional plots, or as reports including combinations of result formats such as graphics, numbers, and text.

Referring now to FIG. 113, an exemplary aspect of a child node (e.g., Joule Heating and Thermal Expansion) is illustrated that branches from an exemplary model node of a model tree. The physics node 11350 includes operations for generating physical quantities 11358 and boundary conditions 11356 for a multiphysics problem, and can be associated with operations for modeling various physics phenomena, such as those described elsewhere herein. Settings for the various illustrated nodes can be accessed and modified by selecting the desired node. For example, the first three child nodes 11352 of the physics node 11350 may represent a sequence of modeling operations that generates default physical quantities for structural displacements, electric potential, and temperature in a geometrical domain. The physical quantities are generated by operations that define thermal expansion (e.g., Thermal Linear Elastic 1 node), conduction of electric current and transport of heat (e.g., Joule Heating Model 1 node), and resistive heating caused by the electric current (e.g., Electromagnetic Heat Source 1 node). The operations generate the default partial differential equations shown for the respective nodes in a selected geometrical domain. The partial differential equations illustrated in FIG. 113 provide exemplary parameters that may be associated with the system being modeled, such as density, ρ, a displacement vector, u, and a stress tensor, σ. The exemplary components of the stress tensor, σ, are functions of the derivatives of the displacement vector. Other exemplary material parameters can include specific heat capacity, C_(P), temperature, T, thermal conductivity, k, electric potential, φ, and electrical conductivity, κ. These physical quantities may be set to an initial value, as illustrated in the exemplary mathematical relationships of FIG. 113. For different model(s), different parameter(s) may be used depending on the engineering or physics phenomenon(a) being simulated—the illustrated physical properties are provided by way of example only, and thus, are non-limiting.

The fourth, fifth, and sixth child nodes 11356 of the physics node 11350 may represent a sequence of modeling operations that generate the default boundary conditions for the multiphysics problem. For example, default boundary conditions may be generated by the operations that define the gradient in the electric potential by setting electric current to zero in the “Electrical Insulation 1” node, the gradient of the temperature by setting the heat flux to zero in the “Thermal Insulation 1” node, and the structural constraints by setting no constraints on the structural displacement at the boundaries in the “Free 1” node. The modeling operations can include generating default equations for the physical quantities interactions at the selected boundaries.

The last exemplary child node 11358 (e.g., Initial Values 1) represents an operation that sets the initial values for all physics quantities, which in the exemplary illustration of FIG. 113 includes temperature, electric potential, and structural displacements. In certain embodiments, the operation may be required as an initial condition for a time-dependent simulation or as an initial guess in a stationary nonlinear simulation. The operation can generate equations for the physical quantities at an initial stage in a selected geometrical domain and may be required by methods that solve partial differential equations.

Referring now to FIG. 114, an exemplary aspect of a window 11452 is illustrated for a model node of a model tree for entering settings that define model operations for a multiphysics problem. More specifically, an exemplary window is illustrated for entering accessed settings for the exemplary Thermal Linear Elastic child node (see, e.g., element 11352 in FIG. 113). Again, the illustration is non-limiting and demonstrates the flexibility of,the model tree for accessing and setting features of the multiphysics modeling system. FIG. 114 includes an exemplary settings window 11452 that is associated with physical quantities for structural displacements that may occur in the modeling of thermal expansion in a selected geometrical domain of a multiphysics problem. In certain embodiments, default physical properties, such as material properties, may be linked to a materials node (see, e.g., material node 11240 in FIG. 112) or a user may manually enter the physical properties. For example, settings window 11452 includes different fields for parameters that can be applicable for generating a contribution to a set of partial differential equations from the Thermal Linear Elastic 1 child node. It is contemplated that the settings window 11452 may define material properties that are then used in generating a node contribution to the partial differential equations for a selected geometrical domain in a multiphysics problem. In the example of FIG. 114, the material properties may include Young's modulus, E, Poisson's ratio, ν, density, ρ, and/or the coefficient of thermal expansion, α, of a material. Applying the exemplary material properties, a node contribution can then be generated as a function of the physical quantities, which for the exemplary embodiment, may be expressed as displacement vector, u. Again, as discussed elsewhere, for different models, different parameters may be used depending on the physics phenomena being simulated—the illustrated material or physical properties are provided by way of example only, and thus, are non-limiting.

In certain embodiments, it is also contemplated that the setting window also displays informational aspects about certain operations in the model tree. For example, information about the author or the source of the operation represented by a particular node in the model tree may be presented or be selectable in the setting window. The setting window may also present information about the date and time (e.g., entry of certain information, running a certain model) or comments regarding the operations about the selected node.

Referring now to FIG. 115, an exemplary aspect of a physics node 11552 associated with a model node is illustrated. The exemplary physics node 11552 has additional nodes 11553, 11554 for describing selected physical quantities for a multiphysics problem. For example, a stress-strain relationship, similar to the one illustrated in FIG. 114, may be altered through the addition of stress tensor, σ. The node denoted “Initial Stress and Strain 1” may change an operation that sets the contribution of the “Thermal Linear Elastic 1”, by changing the stress-strain relationship in a selected geometrical domain. More generally, the sequence of operations can be altered in a multiphysics problem by adding a node further describing certain physical quantities. In certain embodiments, the operation at node 11554 may also change the equations of the physical quantities, such as for the structural displacements, while keeping other equations unchanged. A sequence of operations may be updated by a user by selection of a node, such as node 11554, which may then generate corresponding change(s) in partial differential equation (s) that solve the multiphysics problem. Again, as discussed elsewhere, for different models, different parameters may be used depending on the physics phenomena being simulated—the illustrated nodes are provided by way of example only, and thus, are non-limiting.

Referring now to FIG. 116, another exemplary aspect of a physics node 11650 in a model tree is illustrated. In this aspect, an operation representing contributions to physical quantities is illustrated. For example, child node 11653 (e.g., Heat Source 1) may represent an operation that adds a contribution to a partial differential equation for a physical quantity, such as temperature, in a selected geometrical domain. As FIG. 116 illustrates, the exemplary partial differential equation also includes the temperature contributions represented by the equations from Joule Heating Model 1 and Electromagnetic Heat Source 1. In certain embodiments, child nodes, such as node 11653, may be added by a user to generate contributions for all or some of the physical quantities, such as structural displacements and electric potential, as illustrated in the exemplary physics node 11650 (e.g., Joule Heating and Thermal Expansion). Again, as discussed elsewhere, for different models, different parameters may be used depending on the physics phenomena being simulated—the illustrated nodes are provided by way of example only, and thus, are non-limiting.

Referring now to FIG. 117, an exemplary aspect of a window for adding contributions to the physical quantities associated with a physics node of a model tree is illustrated. A menu box 11755 can be displayed next to a physics node 11750 (e.g., Joule Heating and Thermal Expansion) in response to a system user providing a predetermined input, such as a right-click via a mouse. The menu box 11755 may contain menu items that allow contributions to be added to equations in geometric entities, such as domains, boundaries, edges, and points. In the exemplary aspect, a Heat Source node 11753 contribution may be associated with a heat transfer option in the menu box 11755. For example, by selecting Heat Source node 11753, a contribution may be added to a partial differential equation for temperature in a selected geometrical domain, as illustrated, for example, in FIG. 116. It is contemplated that other selected contributions may be added to other geometric entities depending on the selections made by the multiphysics modeling user. The addition of contributions may also be predetermined as part of a sequence of operations indirectly associated with other model selections.

It is contemplated that in certain aspects of the present disclosure it may be desirable for a multiphysics modeling system to label or otherwise identify nodes of a model tree that represent certain operations that generate contributions to equations associated with a geometrical domain. For example, selecting a node can that represents a load may label or highlight other nodes in the model tree that coexist with that load on any of the load's geometric selections (e.g., domain, boundary, edge, point). A label associated with a non-exclusive node can be used where the operation can coexist with other contributions. If a node represents a contribution that cannot coexist with other nodes on a geometric selection, it can be understood to be an exclusive node. In certain aspects, a last or final node in a sequence may be able overwrite the previous node(s) for the geometric selections where the nodes overlap.

Turning now to FIG. 118, an exemplary model tree is illustrated having a plurality of model nodes that include the identification of exclusive operation(s) associated with a selected node. The exemplary multiphysics model is based on simulating the structural aspects of a structure, such as an actuator, but can be readily applied to any of numerous physics or engineering phenomena. Exemplary Model 1 node includes a physics node 11810 that includes physics quantities and boundary conditions associated with solid mechanics aspects of the virtual structure. In certain exemplary modeling scenarios, it may be desirable to constrain the displacement of a particular structure in one or more directions at a boundary of the solid mechanics physics. To simulate this scenario, the physics quantities and boundaries of the physics node 11810 may include, for example, a fixed boundary condition node 11820 (e.g., Fixed Constraint 1). In certain embodiments, selection of node 11820 may reveal various exclusive associations or relationships with other physics quantity and/or boundary child nodes of the parent physics node 11810. For example, selection of the fixed boundary condition node 11820 can reveal a settings window 11830 that includes exemplary settings for fixed constraints associated with the physics node 11810. Selection of node 11820 may also reveal that the fixed boundary condition associated with node 11820 overrides certain functions associated with the Prescribed Displacement 1 node 11840.

To highlight or identify that node 11840 is overridden by another operation along at least one of its boundaries, a first graphical marker 11845, such as a solid downward facing arrow, may be situated next to the graphical display of node 11840. The settings window 11830 for node 11820 may also display information about the node and the geometric entity that the node 11820 may be acting on. For example, node 11820 is illustrated and described in the settings window 11830 as overriding the Prescribed Displacement 1 node 11840 along boundary number 35.

Selection of fixed boundary condition node 11820 can also reveal an association or relationship with another node, such as Prescribed Acceleration 1 node 11850. The association can be highlighted by a second graphical marker 11855, such as a solid upward facing arrow situated next to the graphical display of node 11850. In certain embodiments, the first and second graphical markers 11845, 11855 may be dynamically displayed in response to a user selecting a particular node, such as node 11820. While both nodes 11840 and 11850 are both associated with node 11820, the association between nodes can be different. For example, the Prescribed Acceleration 1 node 11850 overrides the fixed boundary condition node 11820. This override may be graphically illustrated to the system user by display of an upwardly pointing arrow for second marker 11855 when node 11820 is selected. Furthermore, the settings window 11830 that is displayed upon selection of node 11820 can also display information about the geometric entity that overrides node 11820. For example, node 11820 is illustrated and described in the settings window 11830 as being overridden by the Prescribed Acceleration 1 node 11850 along boundary number 32.

It is contemplated that in certain aspects of the present disclosure, the setting up a model, where certain nodes override other nodes for certain domains, can be done graphically based on the ordering of nodes. Changes to which node overrides another can be made by reordering the nodes. For example, in FIG. 118, node 11840 is overridden by node 11820 based on node 11820 being later on the list of child nodes below physics node 11810. Similarly, node 11850 overrides node 11820 based on node 11850 being later or the lowest on the list of child nodes below physics node 11810. By allowing the reordering of nodes, the model can be adjusted in how one node may or may not override another node.

Based on the exemplary aspects described and illustrated for FIG. 118, it is contemplated that a model tree can include one or more exclusive nodes that override other nodes or operations for one or more domains of a multiphysics problem. For contributions added to an equation that are considered exclusive, the contributions cannot coexist on a geometric domain or boundary with other generated contributions. It is contemplated that it may be desirable for exclusive contributions in the relationships or associations between the various nodes to be graphically presented to a system user. Then, by selecting a particular node (e.g., node 11820), a system user is quickly presented with information in a model tree window 11805 of other nodes (e.g., nodes 11840 and 11850) that are overridden by, or that override, the selected node (e.g., node 11820). These relationships can be illustrated using graphical highlights, markers, or other identifiers. Furthermore, it is contemplated that selection of nodes can also, or alternatively, include the presentation of a setting windows (e.g., setting window 11830) that identifies domains (e.g., geometric entities 32 and 35) to which the exclusive nature of the various relationships or associations between nodes and/or domains may apply.

Referring now to FIG. 119, an exemplary model tree is illustrated having a plurality of model nodes that include the identification of non-exclusive operation(s) associated with a selected node. Similar to FIG. 118, an exemplary multiphysics model based on simulating the structural aspects of a structure, such as an actuator, is illustrated, but the application can be readily applied to any of numerous physics phenomena. Exemplary Model 1 node includes a physics node 11910 that includes physics quantities and boundary conditions associated with solid mechanics aspects for the virtual structure. In the illustrated, non-limiting example, a load can be applied to a boundary, such as the boundary represented by Boundary Load 2 node 11920. Selection of node 11920 may reveal various non-exclusive relationships or associations between node 11920 and other nodes, such as Boundary Load 1 node 11940 and Boundary Load 3 node 11950. The non-exclusive relationship may be that Boundary Load 2 contributes a load, together with Boundary Load 1 and Boundary Load 3, on a particular boundary of the structure being simulated. To highlight the non-exclusive relationship or association between node 11920 and node 11940, a first graphical marker 11945, such as an outline of a downward facing arrow, may be situated next to the graphical display of node 11940 to symbolize that node 11940 contributes together with node 11920 on at least one of the boundaries of the model. The arrow can be directed downward to identify that node 11920 is below node 11940 and that in the sequence of operations, the operation for node 11920 is after the operation for node 11940. To highlight the non-exclusive relationship or association between node 11920 and node 11950, a second graphical marker 11955, such as an outline of an upward facing arrow, may be situated next to the graphical display of node 11950 to symbolize that node 11950 contributes together with node 11920 on at least one of the boundaries of the model. The arrow can be directed upward to identify that node 11920 is above node 11950 and that in the sequence of operations, the operation for node 11920 is before the operation for node 11950. The settings window 11930 for selected node 11920 may also display information about the node(s) and the related non-exclusive operation(s). For example, node 11920 is illustrated and described in the settings window 11930 as contributing with Boundary Load 1 node 11940 along boundary number 111 and as contributing with Boundary Load 3 node 11950 along boundary number 98.

Based on the exemplary aspects described and illustrated for FIG. 119, it is contemplated that a model tree can include one or more non-exclusive nodes or operations that contribute to the same domain or geometric entity of the multiphysics model. It is contemplated that it may be desirable for the non-exclusive contributions in the relationships or associations between the various nodes to be graphically presented to a system user via a GUI. By selecting a particular node (e.g., node 11920), a system user can be quickly presented with information in the model tree window 11905 of other nodes (e.g., nodes 11940 and 11950) that having a contributory affect on the same model domain as the selected node (e.g., node 11920). These relationships can be illustrated using graphical highlights, markers, or other identifiers. Furthermore, it is contemplated that selection of nodes can also, or alternatively, include the presentation of a setting windows (e.g., setting window 11930) that identifies domains (e.g., geometric entities 98 and 111) to which the contributory nature of the various relationships or associations between nodes may apply.

It is contemplated that in certain aspects of the present disclosure, the exemplary model tree window 11905 illustrated in FIG. 119 may include situations in which a node or operation cannot be changed or altered. A system user may also be able to select a particular node or operation and have information associated with the selection displayed, such as in the settings window 11930. Similarly, the model tree window 11905 can allow a system user the ability to review the settings of a multiphysics problem by selecting one geometrical entity at a time, which may allow information about all the nodes or operations that contribute to the equations associated with the selected geometric entity to be obtained. In one non-limiting example, a user may select Boundary Load 2 node 11920, and then select Boundary 98 from the boundary selection list in settings window 11930. Upon selecting Boundary 98, nodes 11920 and 11940 may be highlighted or otherwise identified as contributing to the boundary conditions on Boundary 98. In certain embodiments, a window (not shown) may also be displayed graphically displaying boundary 98 of multiphysics problem with the boundary being highlighted.

Referring now to FIG. 120, an exemplary aspect of a model tree is illustrated comprising a plurality of model nodes 12030, 12080 for which the settings of each of the model nodes can be accessed to allow the formation and solving of a multiphysics problem on a multiphysics modeling system. The model nodes 12030, 12080 may generally represent components of a system being modeled in which the components are simulated simultaneously. In certain embodiments, each of the plurality of models may share some constituents of the multiphysics problem, such as the ones represented by a study node 12060 and a results node 12070. For example, a first model node 12030 (e.g., Thermal Actuator) may represent a thermal actuator activated by an electric current. The electric current may heat a part of the actuator causing thermal expansion, which then yields a desired structural displacement. The electric current may be generated by an amplifier that is also being simulated in the multiphysics problem. The amplifier may be represented in a model tree as a second model node 12080 (e.g., Amplifier). The physical connection between the thermal actuator and the amplifier may be described by an equation that sets a current output from the model of the amplifier equal to the current that drives the thermal actuator. It may also be represented by using a coupling operator, such as an operator that determines the total value of the current at a boundary by integrating the current density over this boundary. The value of this integral, representing the total current, may then be defined in an equation to be equal to the current output from the amplifier. It is contemplated that in certain embodiments more than two model nodes may be simulated by the multiphysics modeling system. As described multiple times elsewhere herein, these exemplary embodiment provide an example only of the model tree features in the multiphysics modeling system and are therefore non-limiting.

An exemplary aspect of the present disclosure includes a method for accessing settings for forming and solving multiphysics problems in a multiphysics modeling system using a model tree. Nodes in the model tree may be used to represent the constituents of a multiphysics problem, such as the geometrical domain, the physical quantities, the physical properties, the boundary conditions, the mesh, the solver, and the simulation results.

In another exemplary aspect of the present disclosure, the model tree may include one or more parent nodes having one or more child nodes. The nodes may represent constituents of the problem to be solved by the modeling. In addition, nodes may further represent sequences of modeling operations that generate constituents when the sequences are performed. Branches in the model tree may represent logical relations between operations represented by parent nodes and child nodes.

In another aspect exemplary aspect of the present disclosure, a method for generating a model tree is based on input(s) entered by a user in a GUI associated with the multiphysics modeling system.

In yet another exemplary aspect of the present disclosure, a method alters operations in a sequence of modeling operations while keeping other operations unchanged. The sequence of modeling operations may then be performed in order to update a multiphysics problem to reflect the altered operations.

In a further exemplary aspect of the present disclosure, a physics node in a model tree may represent a physical quantity and child nodes branching from the physics node may represent operations that add, contributions to the physical quantities. The contributions may describe physical properties and boundary conditions.

In another exemplary aspect of the present disclosure, the contributions may be added to a multiphysics problem when they are attributed to a geometrical domain.

In yet a further exemplary aspect of the present disclosure, method includes several models represented by model nodes in a model tree. The model nodes may represent components that are connected in a system where the several models may be simulated simultaneously. The different models represented in the model tree may share constituents of a multiphysics problem, such as a solver and the simulation results.

As discussed elsewhere herein, the windows, menus, engineering and scientific phenomena, equations, parameters, and nodes illustrated in FIGS. 110-120 are non-limiting examples of model trees contemplated by the present disclosure. It also would be understood in other physics phenomena having different exemplary windows, menus, equations, parameters, and nodes are contemplated by the present disclosure, as well. The windows, menus, equations, parameters, and nodes depend on the components and physics phenomena being modeled. Therefore, it would be understood that FIGS. 110-120 provide non-limiting exemplary relationships for a model tree structure contemplated in a multiphysics modeling system that is capable of simultaneous modeling one or more components having different properties.

According to one exemplary aspect of the present disclosure, a method is executable on one or more processors for implementing a bidirectional link between a design system and a multiphysics modeling system. The method includes the acts of establishing via a communications link a connection between the design system and the multiphysics modeling system. Instructions are communicated via the communication link. The instructions are configured to include commands for generating a geometric representation in the design system based on parameters communicated from the multiphysics modeling system.

It is contemplated that in certain aspects, communicating instructions includes sending and receiving instructions by both the multiphysics modeling system and by the design system. Communicating instructions can also be implemented via dynamic link libraries. The design system and the multiphysics modeling system may each have a separate dynamic link library.

It is further contemplated that in certain aspects, in response to a communicated instruction being received by the design system, files are generated files within the design system that contain a geometric representation. In response to another communicated instruction being received by the multiphysics modeling system, a geometrical domain is generated in the multiphysics modeling system using the files containing the geometric representation and a determined geometric sequence. A multiphysics problem may be defined using the geometrical domain.

It is also contemplated that in certain aspects, in response to a communicated instruction being received by the multiphysics modeling system, parameters are sent for a multiphysics problem from the multiphysics modeling system. The parameters may define geometric features for the design system. In certain aspects, the communicating of instructions includes sending parameter lists representing variations in geometric features.

It is additional contemplated that in certain aspects, physical properties and boundary conditions are determined via associativity for each variation to a defined multiphysics problem.

According to another exemplary aspect of the present disclosure, one or more non-transitory computer readable storage media encoded with instructions executable on one or more processors associated with a bidirectional link between a design system and a multiphysics modeling system. The instructions include the acts of implementing a bidirectional link between a design system and a multiphysics modeling system. The acts further include detecting the design system, and communicating instructions between the detected design system and the multiphysics modeling system. The instructions include commanding the design system to generate a geometric representation based on parameters received from the multiphysics modeling system.

It is contemplated that in certain aspects, the communicating of instructions includes sending and receiving instructions by the multiphysics modeling system or the design system. The communicating of instructions may be implemented via dynamic link libraries. The design system and the multiphysics modeling system may each have a separate dynamic link library.

It is further contemplated that in certain aspects, in response to a communicated instruction being received by the design system, files are generated within the design system that contain a geometric representation. It is also contemplated that in certain aspects, physical properties and boundary conditions are determined via associativity for predetermined variations to a defined multiphysics problem.

According to another exemplary aspect of the present disclosure, a system is configured to establish a bidirectional link between a design system and a multiphysics modeling system. The system includes one or more memory components configured to store a design system dynamic link library and a multiphysics modeling system dynamic link library. A controller is operative to detect an installation of the design system, and implement via the dynamic link libraries, bidirectional communications of instructions between the design system and the multiphysics modeling system.

It is contemplated that in certain aspects, the controller is further operative to generate files within the design system that contain a geometric representation. The controller may further be operative to send parameter lists representing variations in geometric features. In addition, the controller may also be operative to determine, via associativity, physical properties and boundary conditions for each variation to a defined multiphysics problem. In certain aspects, a solution to a defined multiphysics problem may be determined using an iterative process including mapping geometries between each iteration.

According to one exemplary aspect of the present disclosure, a method for controlling settings of a design system is executable on one or more processors associated with the design system. The method includes the acts of detecting via a communications interface a multiphysics modeling system. Instructions are transmitted via the communication interface or another interface. The instructions include model settings related to a multiphysics model at least partially residing in the multiphysics modeling system. Model results are received that are at least partially derived from the transmitted model settings. At least a portion of the received model results are displayed in a graphical user interface associated with the design system.

It is contemplated that in certain aspects, the transmitting and receiving acts are implemented via a bridge connection established between the multiphysics modeling system and the design system. In certain aspects, the multiphysics model is at least partially represented in the graphical user interface via a model tree.

It is further contemplated that in certain aspects, a window is generated in the graphical user interface associated with the design system. The window may be least partially linked with the multiphysics modeling system. A window may also be generated in the graphical user interface associated with the design system. The window may be configured to display model settings via a model tree. The model setting can include at least a portion of the transmitted instructions.

It is also contemplated that in certain aspects, transmitting instructions can include transmitting geometric features. A geometric representation of the multiphysics model may be generated that is at least partially based on the transmitted geometric features. The geometric representation may be generated in the design system.

According to another exemplary aspect of the present disclosure, a method executable on one or more processors associated with a multiphysics modeling system dynamically controls the multiphysics modeling system. The method includes the acts of detecting a design system via a first interface. Instructions are received via one or more interfaces. The instructions include settings related to a multiphysics model associated with the multiphysics modeling system. A solution is determined for the multiphysics model at least partially based on the received instructions. The solution is transmitted to at least one of the one or more interfaces. The solution is configured for display within a design system user interface that is associated with the design system.

It is contemplated that in certain aspects, the receiving and transmitting acts are implemented via a bridge connection between the multiphysics modeling system and the design system.

It is further contemplated that in certain aspects, in response to receiving an instruction associated with a geometric representation, a geometric domain is generated in the multiphysics modeling system. In certain aspects, the act of defining a multiphysics problem may include using the generated geometrical domain.

It is also contemplated that in certain aspects, parameters are transmitted describing geometric features associated with the generated geometrical domain to the design system. In certain aspects, parameter lists are transmitted representing variations in the geometric features.

It is additionally contemplated that in certain aspects, physical properties and boundary conditions are determined, via associativity, for each variation to a defined multiphysics problem.

According to another exemplary aspect of the present disclosure, one or more non-transitory computer readable storage media are encoded with instructions executable on one or more processors associated with a design system. The instructions include the acts of receiving a signal via a communications interface. The signal is associated with a multiphysics modeling system. Instructions are sent to the communications interface or another interface. The instructions include settings related to a multiphysics model associated with the multiphysics modeling system. Multiphysics model results derived from the settings are received. The multiphysics model result are displayed in a design system user interface.

According to a further exemplary aspect of the present disclosure, a method for controlling settings of a design system is executable on one or more processors associated with the design system. The method includes the acts of establishing a communications link between the design system and an associated multiphysics modeling system. Instructions are transmitted via the communications link or another link. The instructions include settings related to a multiphysics model associated with the multiphysics modeling system. Multiphysics model results derived from the settings are received. The multiphysics model results are displayed in a design system user interface.

It is contemplated that in certain aspects, the transmitting and receiving acts are executed via a bridge connection.

It is further contemplated that in certain aspects, the multiphysics model in the design system user interface is represented using a model tree. In certain aspects, a window is generated in the design system user interface that is related to the multiphysics modeling system. The window is associated with the settings and the model tree includes at least a portion of the instructions for the settings.

It is also contemplated that in certain aspects, transmitting instructions includes sending geometric features. In certain aspects, a geometric representation is generated in the design system.

According to another exemplary aspect of the present disclosure, a method for dynamically controlling a multiphysics modeling system is executable on one or more processors associated with the multiphysics modeling system. The method includes the acts of establishing one or more communications channels between the multiphysics modeling system and an associated design system. Instructions are received via the one or more communications channels. The instructions include settings related to a multiphysics model associated with the multiphysics modeling system. An outcome is determined for the multiphysics model based on the received instructions. The outcome is sent to at least one of the one or more communication channels. The outcome is configured for display in a design system user interface.

According to one exemplary aspect of the present disclosure, a method executable on one or more processors associated with a multiphysics modeling system generates a model tree structure for the multiphysics modeling system. The multiphysics modeling system is configured to model combined systems having physical quantities represented in terms of partial differential equations. The method includes the acts of receiving an input associated with a selection of space dimensions for at least one of the combined systems. A plurality of selectable physics options for association with at least one of the combined systems are transmitted for display on a user interface. An input associated with a selection of at least one of the plurality of selectable physics options is received. One or more selectable study options for association with the combined systems are transmitted for display on the user interface. An input associated with a selection of at least one of the one or more selectable study options is received. In response to receiving the input associated with the selection at least one of the one or more selectable study options, a model tree structure is generated. The model tree structure includes a plurality of selectable nodes and subnodes. The selectable nodes and subnodes include fields for storing physical quantities and operations for modeling the combined systems.

It is contemplated that in certain aspects, the selectable nodes and subnodes are configured for display on a user interface associated with the multiphysics modeling system. In certain aspects, the model tree structure includes exclusive and non-exclusive subnodes. The exclusive and non-exclusive subnodes may be labeled with symbols distinguishing the exclusive subnodes from the non-exclusive subnodes and distinguishing the exclusive and non-exclusive subnodes from other subnodes in the model tree.

It is also contemplated that in certain aspects, in response to receiving an input associated with the selection of a node or subnode, an identifying setting of a geometric entity associated with the selected node or subnode is displayed. Information about exclusive or non-exclusive subnodes related to the selected node or subnode may be further displayed.

According to another exemplary aspect of the present disclosure, a method for solving a multiphysics model in a multiphysics modeling system is executed on one or more processor associated with the multiphysics modeling system. a multiphysics modeling system generates a model tree structure for the multiphysics modeling system. The multiphysics model includes combined systems having physical quantities represented in terms of partial differential equations. The multiphysics modeling system is configured to receive model inputs via a model tree. The method includes generating a geometric representation of the combined systems. The geometric representation is at least partially based on data received via a geometry node. Physical properties for the geometric representation of the combined systems are assembled. The physical properties are at least partially based on data received via a materials node. Physics quantities and boundary conditions are assembled for one or both of the geometric representation and the physical properties of the combined systems. The assembling of the physics quantities and boundary conditions are at least partially based on selected physics options received via a physics node. A solution for the multiphysics model of the combined systems is generated. The solution is based on partial differential equations for one or more study steps associated with a set of partial differential equations for the assembled physics quantities and boundary conditions. The study steps are received via a study node. The geometry node, materials node, physics node, and study node are logically associated branches of a model tree for the multiphysics model.

It is contemplated that in certain aspects, exclusive and non-exclusive contributions to the partial differential equations are generated using operations represented by exclusive and non-exclusive child nodes to one or more of the geometry node, the materials node, or the physics node of the model tree. In certain aspects, the exclusive and non-exclusive subnodes are labeled with symbols distinguishing the exclusive subnodes from the non-exclusive child nodes and distinguishing the exclusive and non-exclusive child nodes from other nodes in the model tree.

It is also contemplated that in certain aspects, in response to selecting a node, an identifying setting of a geometric entity associated with the selected node is displayed and information about exclusive or non-exclusive child nodes related to the selected node are further displayed.

It is further contemplated that in certain aspects, the solution is displayed on a user interface and is configured to be displayed in a 2-D graphical form. In certain aspects, the solution is configured to be displayed in a 3-D graphical form or tabular form. In certain aspects, the geometry node, the materials node, the physics node, and the study node are each selectable via a user interface and include fields for storing physical quantities and operations for modeling the combined systems.

According to a further exemplary aspect of the present disclosure, one or more non-transitory computer readable storage media are encoded with instructions executable on one or more processors associated with a multiphysics modeling system. The instructions include the acts of generating a geometric representation of the combined systems. The geometric representation is at least partially based on data received via a geometry node. Physical properties are assembled for the geometric representation of the combined systems. The physical properties are at least partially based on data received via a materials node. Physics quantities and boundary conditions are assembled for one or both of the geometric representation and the physical properties of the combined systems. The assembling of the physics quantities and boundary conditions are at least partially based on selected physics options received via a physics node. A solution is generated for the multiphysics model of the combined systems. The solution is based on partial differential equations for one or more study steps associated with a set of partial differential equations for the assembled physics quantities and boundary conditions. The study steps are received via a study node. The geometry node, materials node, physics node, and study node are logically associated branches of a model tree for the multiphysics model.

According to another aspect of the present disclosure, a method for generating model constituents associated with a multiphysics model via a multiphysics modeling system is executed on one or more processors. The method includes representing a plurality of model constituents as one or more selectable primary nodes of a model tree. Operations that generate the model constituents are represented as one or more selectable secondary nodes to the primary nodes. Physical quantities associated with said model constituents are represented via at least one of the selectable primary nodes of the model tree. Contributions to partial differential equations are generated in the multiphysics modeling system via operations represented as at least one of the selectable secondary nodes to the at least one of the selectable primary nodes.

It is contemplated that in certain aspects, the multiphysics model includes a geometrical domain. The partial differential equations are generated only if attributable to the geometrical domain.

It is also contemplated that in certain aspects the method also includes representing combined systems as a plurality of model nodes in the model tree. Equations operable to couple the plurality of model nodes may be generated via operations represented as secondary nodes to the model nodes.

It is further contemplated that in certain aspects contributions to the partial differential equations are generated for each of the model nodes. The partial differential equations may be solved simultaneously by the multiphysics modeling system.

It is also contemplated that in certain aspects the method also includes generating exclusive and non-exclusive contributions to the partial differential equations using operations represented by exclusive and non-exclusive secondary nodes of the model tree. In certain aspects, the exclusive and non-exclusive subnodes may be labeled with symbols distinguishing the exclusive subnodes from the non-exclusive subnodes and distinguishing the exclusive and non-exclusive secondary nodes from other nodes in the model tree. In certain aspects, in response to selecting a primary node or secondary node, an identifying setting is displayed of a geometric entity associated with the selected node and information about exclusive or non-exclusive secondary nodes related to the selected node may further be displayed.

It is additionally contemplated that the informational aspects about certain operations in the model tree may be displayed for the nodes of the model tree. Information about the author or the source of the operation represented by a particular node in the model tree may be presented or be selectable in the setting window.

According to another aspect of the present disclosure, one or more physical products or systems (e.g., mechanical devices, electrical devices, electromechanical devices, structures, electromagnetic devices, chemical compounds, combinations of one or more of the foregoing) are designed and/or produced using the design system and/or multiphysics modeling system processes and/or methods described herein.

According to yet another aspect of the present disclosure, one or more non-transitory computer readable media are encoded with instructions, which when executed by at least one processor associated with a design system or a multiphysics modeling system, causes the at least one processor to perform the methods described herein.

Each of these embodiments and obvious variations thereof is contemplated as falling within the spirit and scope of the claimed invention, which is set forth in the following claims. 

1. A method executable on one or more processors for implementing a bidirectional link between a design system and a multiphysics modeling system, the method comprising the acts of: establishing via a communications link a connection between the design system and the multiphysics modeling system; communicating instructions via the communication link, wherein the instructions are configured to include commands for generating a geometric representation in the design system based on parameters communicated from the multiphysics modeling system.
 2. The method of claim 1, wherein the communicating instructions includes sending and receiving instructions by both the multiphysics modeling system and by the design system.
 3. The method of claim 1, wherein the communicating of instructions is implemented via dynamic link libraries.
 4. The method of claim 3, wherein, the design system and the multiphysics modeling system each having a separate dynamic link library.
 5. The method of claim 1, further comprising in response to a communicated instruction received by the design system, generating files within the design system that contain a geometric representation.
 6. The method of claim 5, further comprising in response to another communicated instruction received by the multiphysics modeling system, generating a geometrical domain in the multiphysics modeling system using the files containing the geometric representation and a determined geometric sequence.
 7. The method of claim 6, further comprising defining a multiphysics problem using the geometrical domain.
 8. The method of claim 1, further comprising in response to a communicated instruction received by the multiphysics modeling system, sending parameters for a multiphysics problem from the multiphysics modeling system, the parameters defining geometric features for the design system.
 9. The method of claim 1, wherein the communicating of instructions includes sending parameter lists representing variations in geometric features.
 10. The method of claim 9, further comprising determining, via associativity, physical properties and boundary conditions for each variation to a defined multiphysics problem.
 11. One or more non-transitory computer readable storage media encoded with instructions executable on one or more processors associated with a bidirectional link between a design system and a multiphysics modeling system, the instructions including the acts of: detecting the design system; and communicating instructions between the detected design system and the multiphysics modeling system, wherein the instructions include commanding the design system to generate a geometric representation based on parameters received from the multiphysics modeling system.
 12. The one or more non-transitory computer readable media of claim 11, wherein the communicating of instructions includes sending and receiving instructions by the multiphysics modeling system or the design system.
 13. The one or more non-transitory computer readable media of claim 11, wherein the communicating of instructions is implemented via dynamic link libraries.
 14. The one or more non-transitory computer readable media of claim 13, the design system and the multiphysics modeling system each having a separate dynamic link library.
 15. The one or more non-transitory computer readable media of claim 11, further comprising in response to a communicated instruction being received by the design system, generating files within the design system that contain a geometric representation.
 16. The one or more non-transitory computer readable media of claim 11, further comprising determining, via associativity, physical properties and boundary conditions for predetermined variations to a defined multiphysics problem.
 17. A system configured to establish a bidirectional link between a design system and a multiphysics modeling system, the system comprising: one or more memory components configured to store a design system dynamic link library and a multiphysics modeling system dynamic link library; and a controller operative to: detect an installation of the design system, and implement via the dynamic link libraries, bidirectional communications of instructions between the design system and the multiphysics modeling system.
 18. The system of claim 17, wherein the controller is further operative to generate files within the design system that contain a geometric representation.
 19. The system of claim 17, wherein the controller is further operative to send parameter lists representing variations in geometric features.
 20. The system of claim 17, wherein the controller is further operative to determine, via associativity, physical properties and boundary conditions for each variation to a defined multiphysics problem.
 21. The system of claim 17, wherein a solution to a defined multiphysics problem is determined using an iterative process including mapping geometries between each iteration. 